“DIRAC: Neural Image Compression With a Diffusion-Based Decoder”, Goose Et Al 2023

“DIRAC: Neural Image Compression with a Diffusion-Based Decoder”⁠, Noor Fathima Goose, Jens Petersen, Auke Wiggers, Tianlin Xu, Guillaume Sautière2023-01-13 (diffusion model; similar)

“Monolith: Real Time Recommendation System With Collisionless Embedding Table”, Liu Et Al 2022

“Monolith: Real Time Recommendation System With Collisionless Embedding Table”⁠, Zhuoran Liu, Leqi Zou, Xuan Zou, Caihua Wang, Biao Zhang, Da Tang, Bolin Zhu, Yijie Zhu, Peng Wu, Ke Wang2022-09-16 (NN sparsity⁠, AI scaling; similar)

“A Library for Representing Python Programs As Graphs for Machine Learning”, Bieber Et Al 2022

“A Library for Representing Python Programs as Graphs for Machine Learning”⁠, David Bieber, Kensen Shi, Petros Maniatis, Charles Sutton, Vincent Hellendoorn, Daniel Johnson, Daniel Tarlow2022-08-15 (Python; similar)

“TextWorldExpress: Simulating Text Games at One Million Steps Per Second”, Jansen & Côté2022

“TextWorldExpress: Simulating Text Games at One Million Steps Per Second”⁠, Peter A. Jansen, Marc-Alexandre Côté2022-08-01 (text game⁠, RL scaling; backlinks; similar)

“Learning With Combinatorial Optimization Layers: a Probabilistic Approach”, Dalle Et Al 2022

“Learning with Combinatorial Optimization Layers: a Probabilistic Approach”⁠, Guillaume Dalle, Léo Baty, Louis Bouvier, Axel Parmentier2022-07-27 (neural net⁠, model-based RL; similar)

“Overwatch: Learning Patterns in Code Edit Sequences”, Zhang Et Al 2022

“Overwatch: Learning Patterns in Code Edit Sequences”⁠, Yuhao Zhang, Yasharth Bajpai, Priyanshu Gupta, Ameya Ketkar, Miltiadis Allamanis, Titus Barik, Sumit Gulwani2022-07-25 (similar)

“Progress in Mathematical Programming Solvers2001–2020”, Koch Et Al 2022

“Progress in Mathematical Programming Solvers 2001–2020”⁠, Thorsten Koch, Timo Berthold, Jaap Pedersen, Charlie Vanaret2022-06-20 (experience curves; similar)

“DiffC: Lossy Compression With Gaussian Diffusion”, Theis Et Al 2022

“DiffC: Lossy Compression with Gaussian Diffusion”⁠, Lucas Theis, Tim Salimans, Matthew D. Hoffman, Fabian Mentzer2022-06-17 (diffusion model; similar)

“Searching for Cyclic TV Reference Paradoxes”, Pinheiro2022

“Searching for Cyclic TV Reference Paradoxes”⁠, Jamie Pinheiro2022-06-05 (fiction⁠, tech; similar; bibliography)

“Fast Text Placement Scheme for ASCII Art Synthesis”, Chung & Kwon2022

“Fast Text Placement Scheme for ASCII Art Synthesis”⁠, Moonjun Chung, Taesoo Kwon2022-04-14 (anime AI⁠, typography; similar)

“Monarch: Expressive Structured Matrices for Efficient and Accurate Training”, Dao Et Al 2022

“Monarch: Expressive Structured Matrices for Efficient and Accurate Training”⁠, Tri Dao, Beidi Chen, Nimit Sohoni, Arjun Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao2022-04-01 (NN sparsity⁠, AI scaling/hardware; similar; bibliography)

“Maximum Flow and Minimum-Cost Flow in Almost-Linear Time”, Chen Et Al 2022

“Maximum Flow and Minimum-Cost Flow in Almost-Linear Time”⁠, Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva2022-03-01 (similar)

“What Goes into Making an OS to Be Unix Compliant Certified?”, Lambert2022

“What goes into making an OS to be Unix compliant certified?”⁠, Terry Lambert2022-01-14 (backlinks; similar)

“Silent Bugs in Deep Learning Frameworks: An Empirical Study of Keras and TensorFlow”, Tambon Et Al 2021

“Silent Bugs in Deep Learning Frameworks: An Empirical Study of Keras and TensorFlow”⁠, Florian Tambon, Amin Nikanjam, Le An, Foutse Khomh, Giuliano Antoniol2021-12-26 (neural net; similar; bibliography)

“Improving Real-time Rendering of Dynamic Digital Characters in Cycles”, Dietrich2021

“Improving Real-time Rendering of Dynamic Digital Characters in Cycles”⁠, Kévin Dietrich2021-12-10 (economics; backlinks; similar; bibliography)

“Real Time Cluster Path Tracing”, Xie Et Al 2021

“Real Time Cluster Path Tracing”⁠, Feng Xie, Petro Mishchuk, Warren Hunt2021-10-17 (similar)

“Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs”, Sonnerat Et Al 2021

“Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs”⁠, Nicolas Sonnerat, Pengming Wang, Ira Ktena, Sergey Bartunov, Vinod Nair2021-07-21 (RL exploration; similar)

“Real-time Neural Radiance Caching for Path Tracing”, Müller Et Al 2021

“Real-time Neural Radiance Caching for Path Tracing”⁠, Thomas Müller, Fabrice Rousselle, Jan Novák, Alexander Keller2021-06-23 (MLP NN; similar; bibliography)

“Randomness In Neural Network Training: Characterizing The Impact of Tooling”, Zhuang Et Al 2021

“Randomness In Neural Network Training: Characterizing The Impact of Tooling”⁠, Donglin Zhuang, Xingyao Zhang, Shuaiwen Leon Song, Sara Hooker2021-06-22 (neural net⁠, AI safety; similar)

“How Developers Choose Names”, Feitelson Et Al 2021

“How Developers Choose Names”⁠, Dror G. Feitelson, Ayelet Mizrahi, Nofar Noy, Aviad Ben Shabat, Or Eliyahu, Roy Sheffer2021-03-12 (design; similar)

“Pretrained Transformers As Universal Computation Engines”, Lu Et Al 2021

“Pretrained Transformers as Universal Computation Engines”⁠, Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch2021-03-09 (RNN⁠, GPT⁠, AI scaling; backlinks; similar)

“Entropy Trade-offs in Artistic Design: A Case Study of Tamil Kolam”, Tran Et Al 2021

“Entropy trade-offs in artistic design: A case study of Tamil kolam”⁠, N.-Han Tran, Timothy Waring, Silke Atmaca, Bret A. Beheim2021-03-01 (design⁠, novelty U-curve; similar)

“Investment vs. Reward in a Competitive Knapsack Problem”, Neumann & Gros2021

“Investment vs. reward in a competitive knapsack problem”⁠, Oren Neumann, Claudius Gros2021-01-26 (AlphaGo⁠, RL scaling; similar)

“MLGO: a Machine Learning Guided Compiler Optimizations Framework”, Trofin Et Al 2021

“MLGO: a Machine Learning Guided Compiler Optimizations Framework”⁠, Mircea Trofin, Yundi Qian, Eugene Brevdo, Zinan Lin, Krzysztof Choromanski, David Li2021-01-13 (neural net⁠, model-free RL; similar)

“NNUE: The Neural Network of the Stockfish Chess Engine”, Goucher2021

“NNUE: The neural network of the Stockfish chess engine”⁠, Adam P. Goucher2021-01-08 (AI chess⁠, RL scaling; similar)

“I Know What You Bought At Chipotle for $9.81 by Solving A Linear Inverse Problem”, Fleder & Shah2020

“I Know What You Bought At Chipotle for $9.81 by Solving A Linear Inverse Problem”⁠, Michael Fleder, Devavrat Shah2020-12-01 (similar)

“Presyn: Modeling Black-Box Components With Probabilistic Synthesis”, Collie Et Al 2020

“Presyn: Modeling Black-Box Components with Probabilistic Synthesis”⁠, Bruce Collie, Jackson Woodruff, Michael F. P. O’Boyle2020-10-09 (backlinks; similar)

“Why Johnny Won’t Upgrade”, Mattheij2020

“Why Johnny Won’t Upgrade”⁠, Jacques Mattheij2020-08-26 (design; backlinks; similar)

“Optimal Peanut Butter and Banana Sandwiches”, Rosenthal2020

“Optimal Peanut Butter and Banana Sandwiches”⁠, Ethan Rosenthal2020-08-25 (CNN⁠, decision theory; similar; bibliography)

“Measuring Hardware Overhang”, Hippke 2020

“Measuring hardware overhang”⁠, hippke2020-08-05 (AI scaling/hardware⁠, CS/hardware⁠, experience curves⁠, AI chess⁠, RL scaling; backlinks; similar)

“A Time Leap Challenge for SAT Solving”, Fichte Et Al 2020

“A Time Leap Challenge for SAT Solving”⁠, Johannes K. Fichte, Markus Hecher, Stefan Szeider2020-08-05 (AI⁠, CS/hardware⁠, experience curves⁠, model-based RL; backlinks)

“A Bayesian Approach to the Simulation Argument”, Kipping2020

“A Bayesian Approach to the Simulation Argument”⁠, David Kipping2020-08-03 (Bayes; backlinks; similar)

“Lessons Learned from Bugs in Models of Human History”, Ragsdale Et Al 2020

“Lessons learned from bugs in models of human history”⁠, Aaron P. Ragsdale, Dominic Nelson, Simon Gravel, Jerome Kelleher2020-06-05 (human evolution; backlinks; similar)

“Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing”, Dai Et Al 2020

“Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing”⁠, Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le2020-06-05 (RNN⁠, multi-scale Transformer; backlinks; similar)

“The Scaling Hypothesis”, Branwen2020

“The Scaling Hypothesis”⁠, Gwern Branwen2020-05-28 (GPT⁠, AI scaling⁠, insight porn⁠, AI safety⁠, RL scaling⁠, sociology⁠, transhumanism; backlinks; similar; bibliography)

“Measuring the Algorithmic Efficiency of Neural Networks”, Hernandez & Brown2020

“Measuring the Algorithmic Efficiency of Neural Networks”⁠, Danny Hernandez, Tom B. Brown2020-05-08 (CNN⁠, AI scaling⁠, CS/hardware⁠, experience curves; similar)

“Computation in the Human Cerebral Cortex Uses Less Than 0.2 Watts yet This Great Expense Is Optimal When considering Communication Costs”, Levy & Calvert2020

“Computation in the human cerebral cortex uses less than 0.2 watts yet this great expense is optimal when considering communication costs”⁠, William B. Levy, Victoria G. Calvert2020-04-25 (AI scaling/hardware⁠, neuroscience; similar)

“Bringing GNU Emacs to Native Code”, Corallo Et Al 2020

“Bringing GNU Emacs to Native Code”⁠, Andrea Corallo, Luca Nassi, Nicola Manca2020-04-06 (CS/lisp; similar)

“Learning-based Memory Allocation for C++ Server Workloads”, Maas Et Al 2020

“Learning-based Memory Allocation for C++ Server Workloads”⁠, Martin Maas, David G. Andersen, Michael Isard, Mohammad Mahdi Javanmard, Kathryn S. McKinley, Colin Raffel2020-03-16 (RNN; similar)

“The History of the URL”, Bloom2020

“The History of the URL”⁠, Zack Bloom2020-03-05 (design; similar)

“Zip Files: History, Explanation and Implementation”, Wennborg2020

“Zip Files: History, Explanation and Implementation”⁠, Hans Wennborg2020-02-26 (similar)

“Quantifying Independently Reproducible Machine Learning”, Raff2020

“Quantifying Independently Reproducible Machine Learning”⁠, Edward Raff2020-02-06 (neural net⁠, statistics/bias; similar)

“Taxonomy of Real Faults in Deep Learning Systems”, Humbatova Et Al 2019

“Taxonomy of Real Faults in Deep Learning Systems”⁠, Nargiz Humbatova, Gunel Jahangirova, Gabriele Bavota, Vincenzo Riccio, Andrea Stocco, Paolo Tonella2019-11-07 (CNN⁠, AI safety; backlinks; similar)

“They Might Never Tell You It’s Broken”, Chevalier-Boisvert2019

“They Might Never Tell You It’s Broken”⁠, Maxime Chevalier-Boisvert2019-11-02 (design; backlinks; similar; bibliography)

“Hyrum’s Law: An Observation on Software Engineering”, Wright2019

“Hyrum’s Law: An observation on Software Engineering”⁠, Hyrum Wright2019-11 (backlinks; similar; bibliography)

“Grandmaster Level in StarCraft II Using Multi-agent Reinforcement Learning”, Vinyals Et Al 2019

“Grandmaster level in StarCraft II using multi-agent reinforcement learning”⁠, Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung2019-10-30 (AI scaling⁠, AlphaStar⁠, MARL; similar; bibliography)

“Local-First Software: You Own Your Data, in spite of the Cloud [paper]”, Kleppmann Et Al 2019

“Local-First Software: You Own Your Data, in spite of the Cloud [paper]”⁠, Martin Kleppmann, Adam Wiggins, Peter van Hardenberg, Mark McGranaghan2019-10-23 (backlinks; similar)

“Neural Networks Are a Priori Biased towards Boolean Functions With Low Entropy”, Mingard Et Al 2019

“Neural networks are a priori biased towards Boolean functions with low entropy”⁠, Chris Mingard, Joar Skalse, Guillermo Valle-Pérez, David Martínez-Rubio, Vladimir Mikulik, Ard A. Louis2019-09-25 (neural net; similar)

“A Step Toward Quantifying Independently Reproducible Machine Learning Research”, Raff2019

“A Step Toward Quantifying Independently Reproducible Machine Learning Research”⁠, Edward Raff2019-09-14 (neural net; backlinks; similar)

“A View on Deep Reinforcement Learning in System Optimization”, Haj-Ali Et Al 2019

“A View on Deep Reinforcement Learning in System Optimization”⁠, Ameer Haj-Ali, Nesreen K. Ahmed, Ted Willke, Joseph Gonzalez, Krste Asanovic, Ion Stoica2019-08-04 (model-free RL; backlinks; similar)

“Moral Permissibility of Action Plans”, Lindner Et Al 2019

“Moral Permissibility of Action Plans”⁠, Felix Lindner, Robert Mattmüller, Bernhard Nebel2019-07-17 (ethics; similar)

“ParPaRaw: Massively Parallel Parsing of Delimiter-Separated Raw Data”, Stehle & Jacobsen2019

“ParPaRaw: Massively Parallel Parsing of Delimiter-Separated Raw Data”⁠, Elias Stehle, Hans-Arno Jacobsen2019-05-31 (backlinks; similar)

“Real-world Dynamic Programming: Seam Carving”, Das2019

“Real-world dynamic programming: seam carving”⁠, Avik Das2019-05-14 (similar)

“Unraveling the JPEG: JPEG Images Are Everywhere in Our Digital Lives, but behind the Veil of Familiarity Lie Algorithms That Remove Details That Are Imperceptible to the Human Eye. This Produces the Highest Visual Quality With the Smallest File Size—but What Does That Look Like? Let’s See What Our Eyes Can’t See!”, Shehata2019

“Unraveling the JPEG: JPEG images are everywhere in our digital lives, but behind the veil of familiarity lie algorithms that remove details that are imperceptible to the human eye. This produces the highest visual quality with the smallest file size—but what does that look like? Let’s see what our eyes can’t see!”⁠, Omar Shehata2019-05-01 (data visualization; similar)

“Local-first Software: You Own Your Data, in spite of the Cloud [web]”, Kleppmann Et Al 2019

“Local-first software: You own your data, in spite of the cloud [web]”⁠, Martin Kleppmann, Adam Wiggins, Peter van Hardenberg, Mark McGranaghan2019-04 (design; backlinks; similar)

“GAP: Generalizable Approximate Graph Partitioning Framework”, Nazi Et Al 2019

“GAP: Generalizable Approximate Graph Partitioning Framework”⁠, Azade Nazi, Will Hang, Anna Goldie, Sujith Ravi, Azalia Mirhoseini2019-03-02 (AI scaling/hardware; similar)

“Parsing Gigabytes of JSON per Second”, Langdale & Lemire2019

“Parsing Gigabytes of JSON per Second”⁠, Geoff Langdale, Daniel Lemire2019-02-22 (backlinks; similar)

“AutoPhase: Compiler Phase-Ordering for High Level Synthesis With Deep Reinforcement Learning”, Haj-Ali Et Al 2019

“AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning”⁠, Ameer Haj-Ali, Qijing Huang, William Moses, John Xiang, Ion Stoica, Krste Asanovic, John Wawrzynek2019-01-15 (model-free RL; backlinks; similar)

“Test Driving ‘Power of Two Random Choices’ Load Balancing”, Tarreau2019

“Meta-Learning Neural Bloom Filters”, Rae & Al 2019

“Reinventing the Wheel: Discovering the Optimal Rolling Shape With PyTorch”, Wiener2019

“Slow Software”, McGranaghan2018

“Slow Software”⁠, Mark McGranaghan2018-11 (similar)

“Learning to Perform Local Rewriting for Combinatorial Optimization”, Chen & Tian2018

“Learning to Perform Local Rewriting for Combinatorial Optimization”⁠, Xinyun Chen, Yuandong Tian2018-09-30 (model-free RL; backlinks; similar)

“How to Shuffle a Big Dataset”, Hardin2018

“How to shuffle a big dataset”⁠, Chris Hardin2018-09-26 (statistics/probability; similar)

“Deterministic Implementations for Reproducibility in Deep Reinforcement Learning”, Nagarajan Et Al 2018

“Deterministic Implementations for Reproducibility in Deep Reinforcement Learning”⁠, Prabhat Nagarajan, Garrett Warnell, Peter Stone2018-09-15 (model-free RL; backlinks; similar)

“Learning to Optimize Join Queries With Deep Reinforcement Learning”, Krishnan Et Al 2018

“Learning to Optimize Join Queries With Deep Reinforcement Learning”⁠, Sanjay Krishnan, Zongheng Yang, Ken Goldberg, Joseph Hellerstein, Ion Stoica2018-08-09 (model-free RL; backlinks; similar)

“Umineko: The Opium Of The Magics”, Branwen2018

“Umineko: The Opium Of The Magics”⁠, Gwern Branwen2018-07-04 (anime⁠, ethics; backlinks; similar; bibliography)

“Learning to Optimize Tensor Programs”, Chen Et Al 2018

“Learning to Optimize Tensor Programs”⁠, Tianqi Chen, Lianmin Zheng, Eddie Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy2018-05-21 (model-based RL; backlinks; similar)

“Optimizing Query Evaluations Using Reinforcement Learning for Web Search”, Rosset Et Al 2018

“Optimizing Query Evaluations using Reinforcement Learning for Web Search”⁠, Corby Rosset, Damien Jose, Gargi Ghosh, Bhaskar Mitra, Saurabh Tiwary2018-04-12 (model-free RL; backlinks; similar)

“Learning Memory Access Patterns”, Hashemi Et Al 2018

“Learning Memory Access Patterns”⁠, Milad Hashemi, Kevin Swersky, Jamie A. Smith, Grant Ayers, Heiner Litz, Jichuan Chang, Christos Kozyrakis2018-03-06 (RNN⁠, model-free RL; backlinks; similar)

“Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions”, Vasilache Et Al 2018

“Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions”⁠, Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, Priya Goyal, Zachary DeVito, William S. Moses2018-02-13 (AI scaling/hardware; backlinks; similar)

“Innovation and Cumulative Culture through Tweaks and Leaps in Online Programming Contests”, Miu Et Al 2018

“Innovation and cumulative culture through tweaks and leaps in online programming contests”⁠, Elena Miu, Ned Gulley, Kevin N. Laland, Luke Rendell2018 (experience curves⁠, RL exploration⁠, order statistics; similar)

“The Case for Learned Index Structures”, Kraska Et Al 2017

“The Case for Learned Index Structures”⁠, Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis2017-12-04 (model-free RL; backlinks; similar)

“Automatic Differentiation in PyTorch”, Paszke Et Al 2017

“Automatic differentiation in PyTorch”⁠, Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison2017-10-28 (neural net; backlinks; similar)

“From Punched Cards to Flat Screens: A Technical Autobiography”, Hazel2017

“DAG Reduction: Fast Answering Reachability Queries”, Zhou Et Al 2017

“DAG Reduction: Fast Answering Reachability Queries”⁠, Junfeng Zhou, Shijie Zhou, Jeffrey Xu Yu, Hao Wei, Ziyang Chen, Xian Tang2017-05-01 (similar)

“Stochastic Constraint Programming As Reinforcement Learning”, Prestwich Et Al 2017

“Stochastic Constraint Programming as Reinforcement Learning”⁠, Steven Prestwich, Roberto Rossi, Armagan Tarim2017-04-24 (model-based RL; backlinks; similar)

“Learning to Superoptimize Programs”, Bunel Et Al 2017

“Learning to superoptimize programs”⁠, Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr, Pushmeet Kohli2017-02-23 (Codex⁠, meta-learning; similar)

“Web Bloat”, Luu2017

“Web Bloat”⁠, Dan Luu2017-02-08 (DNB; backlinks; similar)

“P≟NP § AI”, Aaronson2017 (page 5)

“P≟NP § AI”⁠, Scott Aaronson2017 (similar)

“Machine Learning for Systems and Systems for Machine Learning”, Dean2017

“Machine Learning for Systems and Systems for Machine Learning”⁠, Jeff Dean2017 (neural net; backlinks)

“Full Resolution Image Compression With Recurrent Neural Networks”, Toderici Et Al 2016

“Full Resolution Image Compression with Recurrent Neural Networks”⁠, George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, Michele Covell2016-08-18 (RNN; similar)

“Energy-Efficient Algorithms”, Demaine Et Al 2016

“Energy-Efficient Algorithms”⁠, Erik D. Demaine, Jayson Lynch, Geronimo J. Mirano, Nirvan Tyagi2016-05-26 (similar)

“A Discrete and Bounded Envy-Free Cake Cutting Protocol for Any Number of Agents”, Aziz & Mackenzie2016

“A Discrete and Bounded Envy-Free Cake Cutting Protocol for Any Number of Agents”⁠, Haris Aziz, Simon Mackenzie2016-04-13 (similar)

“Why WhatsApp Only Needs 50 Engineers for Its 900M Users: One of the (many) Intriguing Parts of the WhatsApp Story Is That It Has Achieved Such Enormous Scale With Such a Tiny Team”, Metz2015

“Why WhatsApp Only Needs 50 Engineers for Its 900M Users: One of the (many) intriguing parts of the WhatsApp story is that it has achieved such enormous scale with such a tiny team”⁠, Cade Metz2015-09-15 (design; backlinks; similar; bibliography)

“Scalability! But at What COST?”, McSherry Et Al 2015

“Scalability! But at what COST?”⁠, Frank McSherry, Michael Isard, Derek G. Murray2015-05 (backlinks; similar)

“Inferring Algorithmic Patterns With Stack-Augmented Recurrent Nets”, Arm Et Al 2015

“Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets”⁠, Arm, Joulin, Tomas Mikolov2015-03-03 (RNN; similar)

“The Ph.D. Grind: A Ph.D. Student Memoir”, Guo2015

“The Ph.D. Grind: A Ph.D. Student Memoir”⁠, Philip Guo2015 (science; backlinks; similar)

“The Mystery Machine: End-to-end Performance Analysis of Large-scale Internet Services”, Chow Et Al 2014

“The Mystery Machine: End-to-end performance analysis of large-scale Internet services”⁠, Michael Chow, David Meisner, Jason Flinn, Daniel Peek, Thomas F. Wenisch2014-10-06 (statistics/causality; backlinks; similar)

“How Inefficient Can a Sort Algorithm Be?”, Lerma2014

“How inefficient can a sort algorithm be?”⁠, Miguel A. Lerma2014-06-03

“Core-Guided MaxSAT With Soft Cardinality Constraints”, Morgado Et Al 2014

“Core-Guided MaxSAT with Soft Cardinality Constraints”⁠, Antonio Morgado, Carmine Dodaro, Joao Marques-Silva2014 (backlinks; similar)

“Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines”, Soler-Toscano Et Al 2014

“Calculating Kolmogorov complexity from the output frequency distributions of small Turing machines”⁠, Fernando Soler-Toscano, Hector Zenil, Jean-Paul Delahaye, Nicolas Gauvrit2014 (similar; bibliography)

“Algorithmic Progress in Six Domains”, Grace2013

“Algorithmic Progress in Six Domains”⁠, Katja Grace2013-12-09 (AI scaling⁠, CS/hardware⁠, experience curves⁠, AI chess⁠, AlphaGo⁠, RL scaling; similar)

“Intelligence Explosion Microeconomics”, Yudkowsky2013

“Intelligence Explosion Microeconomics”⁠, Eliezer Yudkowsky2013-09-13 (AI scaling⁠, CS/hardware⁠, experience curves⁠, AI safety; similar)

“Bounded Kolmogorov Complexity Based on Cognitive Models”, Strannegård Et Al 2013

“Bounded Kolmogorov Complexity Based on Cognitive Models”⁠, Claes Strannegård, Abdul Rahim Nizamani, Anders Sjöberg, Fredrik Engström2013-01 (AI; similar)

“Evaluating the Design of the R Language: Objects and Functions for Data Analysis”, Morandat Et Al 2012

“Evaluating the Design of the R Language: Objects and Functions for Data Analysis”⁠, Floreal Morandat, Brandon Hill, Leo Osvald, Jan Vitek2012-06-11 (design; similar)

“The International SAT Solver Competitions”, Järvisalo Et Al 2012

“The International SAT Solver Competitions”⁠, Matti Järvisalo, Daniel Le Berre, Olivier Roussel, Laurent Simon2012-03-15 (AI⁠, CS/hardware⁠, experience curves; backlinks; similar)

“National Cryptologic Museum Opens New Exhibit on Dr. John Nash”, NSA 2012

“National Cryptologic Museum Opens New Exhibit on Dr. John Nash”⁠, NSA2012-01-27 (crypto; backlinks; similar)

“A Brief History of NP-Completeness, 1954–2012”, Johnson2012

“A Brief History of NP-Completeness, 1954–2012”⁠, David S. Johnson2012 (backlinks; similar)

“STEPS Toward Expressive Programming Systems:”A Science Experiment”“, Ohshima Et Al 2012 (page 2)

“STEPS Toward Expressive Programming Systems: "A Science Experiment"”⁠, Yoshiki Ohshima, Dan Amelang, Ted Kaehler, Bert Freudenberg, Aran Lunzer, Alan Kay, Ian Piumarta, Takashi Yamamiya2012 (design⁠, philosophy; similar)

“A Cross-Language Perspective On Speech Information Rate”, Pellegrino Et Al 2011

“A Cross-Language Perspective On Speech Information Rate”⁠, François Pellegrino, Christophe Coupé, Egidio Marsico2011-09 (psychology; backlinks)

“Why Philosophers Should Care About Computational Complexity”, Aaronson2011

“Why Philosophers Should Care About Computational Complexity”⁠, Scott Aaronson2011-08-08 (AI⁠, philosophy/epistemology⁠, philosophy/logic⁠, philosophy/mind; backlinks; similar)

“Notes on a New Philosophy of Empirical Science”, Burfoot2011

“Notes on a New Philosophy of Empirical Science”⁠, Daniel Burfoot2011-04-28 (philosophy/epistemology⁠, statistics/bias; backlinks; similar)

“New Strategy of Lossy Text Compression”, Al-Dubaee & Ahmad2010

“New Strategy of Lossy Text Compression”⁠, Shawki A. Al-Dubaee, Nesar Ahmad2010-08-05 (similar)

“You’re Doing It Wrong: Think You’ve Mastered the Art of Server Performance? Think Again.”, Kamp2010

“You’re Doing It Wrong: Think you’ve mastered the art of server performance? Think again.”⁠, Poul-Henning Kamp2010-06-11 (backlinks; similar)

“Formal Theory of Creativity & Fun & Intrinsic Motivation (1990–2010)”, Schmidhuber2010

“Coolex: The Coolest Way to Generate Combinations”, Ruskey & Williams2009

“Coolex: The coolest way to generate combinations”⁠, Frank Ruskey, Aaron Williams2009-09-06 (math; similar)

“De-anonymizing Social Networks”, Narayanan & Shmatikov2009

“De-anonymizing Social Networks”⁠, Arvind Narayanan, Vitaly Shmatikov2009-05-17 (backlinks; similar)

“The Gödel Letter”, Gödel2009

“The Gödel Letter”⁠, Kurt Gödel2009-04-02 (math; backlinks; similar)

“Producing Wrong Data Without Doing Anything Obviously Wrong!”, Mytkowicz Et Al 2009

“Producing Wrong Data Without Doing Anything Obviously Wrong!”⁠, Todd Mytkowicz, Amer Diwan, Matthias Hauswirth, Peter F. Sweeney2009-03-07 (statistics/bias; backlinks; similar)

“Is There A Fourth Futamura Projection?”, Robert2009

“Dual-Pivot Quicksort Algorithm”, Yaroslavskiy2009

“Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes”, Schmidhuber2008

“Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes”⁠, Juergen Schmidhuber2008-12-23 (novelty U-curve⁠, RL exploration; similar)

“Aggregating Inconsistent Information: Ranking and Clustering”, Ailon Et Al 2008

“Aggregating inconsistent information: Ranking and clustering”⁠, Nir Ailon, Moses Charikar, Alantha Newman2008-11 (order statistics/comparison; backlinks; similar)

“Interview With Donald Knuth”, Binstock2008

“Interview with Donald Knuth”⁠, Andrew Binstock2008-04-25 (T_eX; backlinks; similar; bibliography)

“Optimal Boarding Method for Airline Passengers”, Steffen2008

“Optimal boarding method for airline passengers”⁠, Jason H. Steffen2008-02-06 (similar)

“Harnessing Vision for Computation”, Changizi2008

“Harnessing Vision for Computation”⁠, Mark Changizi2008 (neuroscience⁠, psych/vision; backlinks)

“How To Break Anonymity of the Netflix Prize Dataset”, Narayanan & Shmatikov2006

“How To Break Anonymity of the Netflix Prize Dataset”⁠, Arvind Narayanan, Vitaly Shmatikov2006-10-18 (CS/security; backlinks; similar)

“Oral History of Butler Lampson § WWW”, Lampson & Kay2006 (page 36)

“Oral History of Butler Lampson § WWW”⁠, Butler Lampson, Alan Kay2006-08-22 (Bitcoin⁠, CS/security⁠, history; similar; bibliography)

“History of Combinatorial Generation (The Art of Computer Programming: Volume 4: Pre-Fascicle 4B: §7.2.1.7)”, Knuth2005

“NP-complete Problems and Physical Reality”, Aaronson2005

“NP-complete Problems and Physical Reality”⁠, Scott Aaronson2005-02-12 (science; similar)

“Lower-Stretch Spanning Trees”, Elkin Et Al 2004

“Lower-Stretch Spanning Trees”⁠, Michael Elkin, Yuval Emek, Daniel A. Spielman, Shang-Hua Teng2004-11-17 (backlinks)

“A Short History of Computational Complexity”, Fortnow Et Al 2003

“Least Effort and the Origins of Scaling in Human Language”, Cancho & Sole2003

“Least effort and the origins of scaling in human language”⁠, Ramon Ferrer i Cancho, Ricard V. Sole2003 (psychology; backlinks; similar)

“Solving Real-World Linear Programs: A Decade and More of Progress”, Bixby2002

“Solving Real-World Linear Programs: A Decade and More of Progress”⁠, Robert E. Bixby2002-02-01 (experience curves; similar)

“A Bit-Vector Algorithm for Computing Levenshtein and Damerau Edit Distances”, Hyyrö2002

“A Bit-Vector Algorithm for Computing Levenshtein and Damerau Edit Distances”⁠, Heikki Hyyrö2002-01 (similar)

“Estimating and Comparing Entropy across Written Natural Languages Using PPM Compression”, Behr Et Al 2002

“Estimating and Comparing Entropy across Written Natural Languages Using PPM Compression”⁠, Frederic H. Behr Junior, Victoria Fossum, Michael Mitzenmacher, David Xiao2002 (psychology; backlinks; similar)

“Naked Objects: a Technique for Designing More Expressive Systems”, Pawson & Matthews2001

“Naked objects: a technique for designing more expressive systems”⁠, Richard Pawson, Robert Matthews2001-12-01 (typography; similar)

“On Proebsting’s Law”, Scott2001

“On Proebsting's Law”⁠, Kevin Scott2001-03-01 (CS/hardware⁠, experience curves; backlinks; similar)

“Peopleware: Why Measure Performance”, DeMarco & Lister2001

“The Effects of Moore’s Law and Slacking on Large Computations”, Gottbrath Et Al 1999

“The Effects of Moore’s Law and Slacking on Large Computations”⁠, C Gottbrath, J. Bailin, C. Meakin, T. Thompson, J. J. Charfman1999-12-09 (experience curves; backlinks)

“The Physical Limits of Communication”, Lachmann Et Al 1999

“The physical limits of communication”⁠, Michael Lachmann, M. E. J. Newman, Cristopher Moore1999-07-30 (similar)

“Quantum Effects in Algorithms”, Jozsa1998

“Quantum Effects in Algorithms”⁠, Richard Jozsa1998-05-29 (science; backlinks; similar)

“Applications of Randomness in System Performance Measurement”, Blackwell1998

“Applications of Randomness in System Performance Measurement”⁠, Trevor Leslie Blackwell1998-05 (statistics/bias; backlinks; similar)

“Proebsting’s Law: Compiler Advances Double Computing Power Every 18 Years”, Proebsting1998

“Proebsting’s Law: Compiler Advances Double Computing Power Every 18 Years”⁠, Todd Proebsting1998 (CS/hardware⁠, experience curves; backlinks; similar)

“THE ENTROPY OF ENGLISH USING PPM-BASED MODELS—Data Compression Conference, 1996. DCC ’96. Proceedings”

“Entropy of Natural Languages: Theory and Experiment”, Levitin & Reingold1994

“Entropy of natural languages: Theory and experiment”⁠, Lev B. Levitin, Zeev Reingold1994-05-01 (similar)

“Building a Large Annotated Corpus of English: The Penn Treebank”, Marcus Et Al 1993

“Building a Large Annotated Corpus of English: The Penn Treebank”⁠, Mitchell Marcus, Beatrice Santorini, Mary Ann Marcinkiewicz1993-10-01 (AI scaling; backlinks)

“Separating Strings With Small Automata”, Robson1989

“Optimal Nonlinear Approximation”, DeVore Et Al 1989

“Optimal Nonlinear Approximation”⁠, Ronald A. DeVore, Ralph Howard, Charles Micchelli1989

“Hypertext and the Oxford English Dictionary”, Raymond & Tompa1988

“Hypertext and the Oxford English dictionary”⁠, Darrel R. Raymond, Frank William Tompa1988-07-01 (typography)

“Average Case Complete Problems”, Levin1986

“Average Case Complete Problems”⁠, Leonid A. Levin1986-02-01 (backlinks; similar)

“Probabilistic Counting Algorithms for Data Base Applications”, Flajolet & Martin1985

“Probabilistic counting algorithms for data base applications”⁠, Philippe Flajolet, G. Nigel Martin1985-10 (backlinks; similar)

“Randomness Conservation Inequalities; Information and Independence in Mathematical Theories”, Levin1984

“Randomness conservation inequalities; information and independence in mathematical theories”⁠, Leonid A. Levin1984-04 (AI⁠, statistics/probability; backlinks; similar)

“Epigrams on Programming”, Perlis1982

“Epigrams on Programming”⁠, Alan J. Perlis1982-09 (AI⁠, design⁠, humor⁠, philosophy; backlinks; similar)

“Procedural Reflection in Programming Languages”, Smith1982

“Procedural Reflection in Programming Languages”⁠, Brian Cantwell Smith1982-02 (CS/lisp; similar)

“On Holy Wars and a Plea for Peace”, Cohen1981

“On Holy Wars and a Plea for Peace”⁠, Daniel Cohen1981-10-01 (backlinks; similar)

“Mutation Analysis Of Program Test Data”, Budd1980

“Mutation Analysis Of Program Test Data”⁠, Timothy Alan Budd1980-05 (CS/lisp; similar; bibliography)

“A Correct Preprocessing Algorithm for Boyer-Moore String-Searching”, Rytter1980

“A Correct Preprocessing Algorithm for Boyer-Moore String-Searching”⁠, Wojciech Rytter1980

“A Convergent Gambling Estimate Of The Entropy Of English”, Cover & King1978

“A Convergent Gambling Estimate Of The Entropy Of English”⁠, Thomas M. Cover, Roger C. King1978-07-01 (psychology⁠, statistics/probability; backlinks; similar)

“Algorithms for Loop Matchings”, Nussinov Et Al 1978

“Algorithms for Loop Matchings”⁠, Ruth Nussinov, George Pieczenik, Jerrold R. Griggs, Daniel J. Kleitman1978-01 (similar)

“Fast Pattern Matching in Strings”, Knuth Et Al 1977

“Fast Pattern Matching in Strings”⁠, Donald E. Knuth, James H. Morris Junior, Vaughan R. Pratt1977-06-01 (backlinks; similar)

“Structured Programming With go To Statements”, Knuth1974

“Structured Programming with go to Statements”⁠, Donald E. Knuth1974-12 (backlinks; similar)

“A Parallel Algorithm for the Efficient Solution of a General Class of Recurrence Equations”, Kogge & Stone1973

“A Parallel Algorithm for the Efficient Solution of a General Class of Recurrence Equations”⁠, Peter M. Kogge, Harold S. Stone1973-08 (similar)

“The Dangers of Computer-Science Theory”, Knuth1973

“The Dangers of Computer-Science Theory”⁠, Donald E. Knuth1973 (math; backlinks; similar)

“Universal Sequential Search Problems”, Levin1973

“Universal Sequential Search Problems”⁠, L. A. Levin1973 (AI; backlinks)

“The Humble Programmer [EWD340]”, Dijkstra1972

“The Humble Programmer [EWD340]”⁠, Edsger W. Dijkstra1972 (math; backlinks; similar)

“A Simple Randomization Procedure”, Sandelius1962

“A Simple Randomization Procedure”⁠, Martin Sandelius1962-07-01 (statistics/probability; backlinks; similar)

“Generation of Random Permutations of Given Number of Elements Using Random Sampling Numbers”, Rao1961

“Generation of Random Permutations of Given Number of Elements Using Random Sampling Numbers”⁠, C. Radhakrishna Rao1961-08-01 (statistics/probability; backlinks; similar)

“Possible Principles Underlying the Transformations of Sensory Messages”, Barlow1961

“Possible Principles Underlying the Transformations of Sensory Messages”⁠, H. B. Barlow1961 (neuroscience⁠, psych/vision; similar; bibliography)

“Coding Theorems for a Discrete Source With a Fidelity Criterion”, Shannon1959

“Coding Theorems for a Discrete Source With a Fidelity Criterion”⁠, Claude Shannon1959 (AI; backlinks; similar)

“The Codeless Code: Case 96:”Stateless” ”

“Submission #6347: Chef Stef’s NES Arkanoid ‘Warpless’ In 11:11.18”

“TSP Art”

Wikipedia

1. Algorithmic information theory

2. Boyer-Moore string-search algorithm

3. Fibonacci word

4. Hashlife

5. Huffman coding

6. LZ77 and LZ78

7. List of lists of lists

8. Logical depth

9. Splay tree

10. Suffix array