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Learning Theory

5,312 papers

Papers per year

Papers

Specializing Pre-trained Language Models for Better Relational Reasoning via Network Pruning NAACL 2022
Transductive Robust Learning Guarantees AISTATS 2022
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm AISTATS 2022
Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness NIPS 2022
Domain Generalization through the Lens of Angular Invariance IJCAI 2022
An Initial Alignment between Neural Network and Target is Needed for Gradient Descent to Learn ICML 2022
On the probability–quality paradox in language generation ACL 2022
Adversarial Robustness is at Odds with Lazy Training NIPS 2022
Principal Components Bias in Over-parameterized Linear Models, and its Manifestation in Deep Neural Networks JMLR 2022
On the Learning of Non-Autoregressive Transformers ICML 2022
Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions NIPS 2022
Cascaded Gaps: Towards Logarithmic Regret for Risk-Sensitive Reinforcement Learning ICML 2022
Spectral Pruning for Recurrent Neural Networks AISTATS 2022
On the Complexity of Inductively Learning Guarded Clauses AAAI 2022
PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency AISTATS 2022
Extracting Operator Trees from Model Embeddings EMNLP 2022
Does Momentum Change the Implicit Regularization on Separable Data? NIPS 2022
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks CVPR 2022
High-probability bounds for robust stochastic Frank-Wolfe algorithm UAI 2022
Learning Continuous Graph Structure with Bilevel Programming for Graph Neural Networks IJCAI 2022
Phase transitions in when feedback is useful NIPS 2022
Augmented RBMLE-UCB Approach for Adaptive Control of Linear Quadratic Systems NIPS 2022
Vision Transformers provably learn spatial structure NIPS 2022
Instance-optimal PAC Algorithms for Contextual Bandits NIPS 2022
Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers NIPS 2022