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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
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Learning Theory
5312 directly classified papers
Papers per year
2001: 1
2002: 16
2003: 16
2004: 15
2005: 17
2006: 30
2007: 32
2008: 32
2009: 34
2010: 66
2011: 76
2012: 74
2013: 94
2014: 115
2015: 123
2016: 128
2017: 185
2018: 219
2019: 390
2020: 466
2021: 640
2022: 664
2023: 799
2024: 688
2025: 307
2026: 85
Papers
Shifted PAUQ: Distribution shift in text-to-SQL
EMNLP 2023
Understanding Representation Learnability of Nonlinear Self-Supervised Learning
AAAI 2023
On the Sample Complexity of Representation Learning in Multi-Task Bandits with Global and Local Structure
AAAI 2023
Approximating Full Conformal Prediction at Scale via Influence Functions
AAAI 2023
False Discovery Proportion control for aggregated Knockoffs
NIPS 2023
Which Shortcut Solution Do Question Answering Models Prefer to Learn?
AAAI 2023
Bandit Submodular Maximization for Multi-Robot Coordination in Unpredictable and Partially Observable Environments
RSS 2023
On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization
AAAI 2023
Koala: An Index for Quantifying Overlaps with Pre-training Corpora
EMNLP 2023
Learn to Accumulate Evidence from All Training Samples: Theory and Practice
ICML 2023
Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization
EMNLP 2023
Exploring the Cognitive Knowledge Structure of Large Language Models: An Educational Diagnostic Assessment Approach
EMNLP 2023
Data Similarity is Not Enough to Explain Language Model Performance
EMNLP 2023
Can Pretrained Language Models (Yet) Reason Deductively?
EACL 2023
How do languages influence each other? Studying cross-lingual data sharing during LM fine-tuning
EMNLP 2023
Open problem: log(n) factor in "Local Glivenko-Cantelli"
COLT 2023
Inverse Scaling Can Become U-Shaped
EMNLP 2023
How Powerful are Shallow Neural Networks with Bandlimited Random Weights?
ICML 2023
Learning Hidden Markov Models Using Conditional Samples
COLT 2023
Have LLMs Advanced Enough? A Challenging Problem Solving Benchmark For Large Language Models
EMNLP 2023
Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique
COLT 2023
Local Risk Bounds for Statistical Aggregation
COLT 2023
Improper Multiclass Boosting
COLT 2023
GLEN: Generative Retrieval via Lexical Index Learning
EMNLP 2023
Instance-Optimality in Interactive Decision Making: Toward a Non-Asymptotic Theory
COLT 2023
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