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Learning Theory

5,334 papers

Papers per year

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Papers

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning ICML 2020
ConQUR: Mitigating Delusional Bias in Deep Q-Learning ICML 2020
The Many Shapley Values for Model Explanation ICML 2020
No-Regret Exploration in Goal-Oriented Reinforcement Learning ICML 2020
Student Specialization in Deep Rectified Networks With Finite Width and Input Dimension ICML 2020
Sequential Transfer in Reinforcement Learning with a Generative Model ICML 2020
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis ICML 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020
Disentangling Trainability and Generalization in Deep Neural Networks ICML 2020
Maximum-and-Concatenation Networks ICML 2020
A Finite-Time Analysis of Q-Learning with Neural Network Function Approximation ICML 2020
Rethinking Bias-Variance Trade-off for Generalization of Neural Networks ICML 2020
It’s Not What Machines Can Learn, It’s What We Cannot Teach ICML 2020
Learning Near Optimal Policies with Low Inherent Bellman Error ICML 2020
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case ICML 2020
Learning with Feature and Distribution Evolvable Streams ICML 2020
Error-Bounded Correction of Noisy Labels ICML 2020
Best Arm Identification for Cascading Bandits in the Fixed Confidence Setting ICML 2020
When Demands Evolve Larger and Noisier: Learning and Earning in a Growing Environment ICML 2020
Concentration of Distortion: The Value of Extra Voters in Randomized Social Choice IJCAI 2020
Efficient Algorithms for Learning Revenue-Maximizing Two-Part Tariffs IJCAI 2020
Deep Learning for Abstract Argumentation Semantics IJCAI 2020
On the Learnability of Possibilistic Theories IJCAI 2020
Best Arm Identification in Spectral Bandits IJCAI 2020
Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space IJCAI 2020