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The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning

International Conference on Machine Learning (ICML), 2023

11 April 2023

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Papers citing "The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning"

37 / 37 papers shown

Title
Self-Adaptive Graph Mixture of Models Mohit Meena Yash Punjabi Abhishek A Vishal Sharma Mahesh Chandran 104 0 0 17 Nov 2025
A Survey of Inductive Reasoning for Large Language Models Kedi Chen Dezhao Ruan Yuhao Dan Y. Wang Siyu Yan ... Biqing Qi Linyang Li Qipeng Guo Xiaoming Shi Wei-na Zhang LRM 70 3 0 11 Oct 2025
Bridging Kolmogorov Complexity and Deep Learning: Asymptotically Optimal Description Length Objectives for Transformers Peter Shaw James Cohan Jacob Eisenstein Kristina Toutanova 154 0 0 26 Sep 2025
Exploiting Vocabulary Frequency Imbalance in Language Model Pre-training Woojin Chung Jeonghoon Kim 144 0 0 21 Aug 2025
Foundations of Interpretable Models Pietro Barbiero M. Zarlenga Alberto Termine M. Jamnik Giuseppe Marra AI4CE 93 0 0 01 Aug 2025
Overfitting has a limitation: a model-independent generalization gap bound based on Rényi entropy Atsushi Suzuki Jing Wang 161 0 0 30 May 2025
Characterising the Inductive Biases of Neural Networks on Boolean Data Chris Mingard Lukas Seier Niclas Goring Andrei-Vlad Badelita Charles London Ard A. Louis AI4CE 220 1 0 29 May 2025
Variational Deep Learning via Implicit Regularization Jonathan Wenger Beau Coker Juraj Marusic John P. Cunningham OOD UQCV BDL 256 1 0 26 May 2025
Constant Bit-size Transformers Are Turing Complete Qian Li Yuyi Wang LRM 117 1 0 22 May 2025
A Mathematical Philosophy of Explanations in Mechanistic Interpretability -- The Strange Science Part I.i Kola Ayonrinde Louis Jaburi MILM 418 3 0 01 May 2025
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the WildComputer Vision and Pattern Recognition (CVPR), 2025 Damien Teney Liangze Jiang Florin Gogianu Ehsan Abbasnejad 946 4 0 13 Mar 2025
Deep Learning is Not So Mysterious or Different Andrew Gordon Wilson 273 21 0 03 Mar 2025
A Complexity-Based Theory of Compositionality Eric Elmoznino Thomas Jiralerspong Yoshua Bengio Guillaume Lajoie CoGe 618 17 0 18 Oct 2024
In-context learning and Occam's razor Eric Elmoznino Tom Marty Tejas Kasetty Léo Gagnon Sarthak Mittal Mahan Fathi Dhanya Sridhar Guillaume Lajoie 440 4 0 17 Oct 2024
OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable? Liangze Jiang Damien Teney OODD OOD 487 1 0 03 Oct 2024
Grand Challenges in Bayesian Computation Anirban Bhattacharya Antonio Linero Chris. J. Oates 163 3 0 01 Oct 2024
Understanding Simplicity Bias towards Compositional Mappings via Learning Dynamics Yi Ren Danica J. Sutherland CoGe 151 6 0 15 Sep 2024
Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts Anna Mészáros Szilvia Ujváry Wieland Brendel Patrik Reizinger Ferenc Huszár 211 1 0 09 Sep 2024
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models Sanae Lotfi Yilun Kuang Brandon Amos Micah Goldblum Marc Finzi Andrew Gordon Wilson 168 14 0 25 Jul 2024
Understanding Visual Feature Reliance through the Lens of Complexity Thomas Fel Louis Bethune Andrew Kyle Lampinen Thomas Serre Katherine Hermann FAtt CoGe 207 14 0 08 Jul 2024
Artificial Inductive Bias for Synthetic Tabular Data Generation in Data-Scarce Scenarios Patricia A. Apellániz Ana Jiménez Borja Arroyo Galende J. Parras Santiago Zazo 339 1 0 03 Jul 2024
Implicit Multimodal Alignment: On the Generalization of Frozen LLMs to Multimodal Inputs Mustafa Shukor Matthieu Cord 225 11 0 26 May 2024
The Platonic Representation HypothesisInternational Conference on Machine Learning (ICML), 2024 Minyoung Huh Brian Cheung Tongzhou Wang Phillip Isola 566 224 0 13 May 2024
Demystifying the Hypercomplex: Inductive Biases in Hypercomplex Deep Learning Danilo Comminiello Eleonora Grassucci Danilo P. Mandic A. Uncini HAI AI4CE 200 4 0 11 May 2024
Analyzing the Role of Semantic Representations in the Era of Large Language ModelsNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024 Zhijing Jin Yuen Chen Fernando Gonzalez Jiarui Liu Jiayi Zhang Julian Michael Bernhard Schölkopf Mona T. Diab 192 14 0 02 May 2024
Rethinking LLM Memorization through the Lens of Adversarial Compression Avi Schwarzschild Zhili Feng Pratyush Maini Zachary Chase Lipton J. Zico Kolter 394 84 0 23 Apr 2024
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 499 33 0 04 Mar 2024
Fine-Tuned Language Models Generate Stable Inorganic Materials as TextInternational Conference on Learning Representations (ICLR), 2024 Nate Gruver Anuroop Sriram Andrea Madotto A. Wilson C. L. Zitnick Zachary W. Ulissi 224 99 0 06 Feb 2024
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate Can Jin Tong Che Hongwu Peng Yiyuan Li Dimitris N. Metaxas Marco Pavone 308 55 0 05 Feb 2024
EXMOS: Explanatory Model Steering Through Multifaceted Explanations and Data Configurations Aditya Bhattacharya Simone Stumpf Lucija Gosak Gregor Stiglic K. Verbert 169 29 0 01 Feb 2024
Non-Vacuous Generalization Bounds for Large Language Models Sanae Lotfi Marc Finzi Yilun Kuang Tim G. J. Rudner Micah Goldblum Andrew Gordon Wilson 429 37 0 28 Dec 2023
Perspectives on the State and Future of Deep Learning - 2023 Micah Goldblum A. Anandkumar Richard Baraniuk Tom Goldstein Kyunghyun Cho Zachary Chase Lipton Melanie Mitchell Preetum Nakkiran Max Welling Andrew Gordon Wilson 343 5 0 07 Dec 2023
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision TasksNeural Information Processing Systems (NeurIPS), 2023 Micah Goldblum Hossein Souri Renkun Ni Manli Shu Viraj Prabhu ... Adrien Bardes Judy Hoffman Ramalingam Chellappa Andrew Gordon Wilson Tom Goldstein VLM 375 90 0 30 Oct 2023
In-Context Learning Dynamics with Random Binary SequencesInternational Conference on Learning Representations (ICLR), 2023 Eric J. Bigelow Ekdeep Singh Lubana Robert P. Dick Hidenori Tanaka T. Ullman 300 12 0 26 Oct 2023
Large Language Models Are Zero-Shot Time Series ForecastersNeural Information Processing Systems (NeurIPS), 2023 Nate Gruver Marc Finzi Shikai Qiu Andrew Gordon Wilson AI4TS 270 552 0 11 Oct 2023
In-Context Learning through the Bayesian PrismInternational Conference on Learning Representations (ICLR), 2023 Madhuri Panwar Kabir Ahuja Navin Goyal BDL 238 66 0 08 Jun 2023
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and RegressionInternational Conference on Learning Representations (ICLR), 2023 Runtian Zhai Bing Liu Andrej Risteski Zico Kolter Pradeep Ravikumar SSL 287 17 0 01 Jun 2023