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Theory

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Papers

Learning Interaction Kernels for Agent Systems on Riemannian Manifolds ICML 2021
Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity ICML 2021
Near-Optimal Model-Free Reinforcement Learning in Non-Stationary Episodic MDPs ICML 2021
Adaptive Sampling for Best Policy Identification in Markov Decision Processes ICML 2021
Fundamental Tradeoffs in Distributionally Adversarial Training ICML 2021
On the Explicit Role of Initialization on the Convergence and Implicit Bias of Overparametrized Linear Networks ICML 2021
Connecting Interpretability and Robustness in Decision Trees through Separation ICML 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks ICML 2021
WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points ICML 2021
Bias-Free Scalable Gaussian Processes via Randomized Truncations ICML 2021
Implicit Regularization in Tensor Factorization ICML 2021
On Linear Identifiability of Learned Representations ICML 2021
Discretization Drift in Two-Player Games ICML 2021
UnICORNN: A recurrent model for learning very long time dependencies ICML 2021
Asymptotics of Ridge Regression in Convolutional Models ICML 2021
State Relevance for Off-Policy Evaluation ICML 2021
A Precise Performance Analysis of Support Vector Regression ICML 2021
Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances ICML 2021
Generalization Error Bound for Hyperbolic Ordinal Embedding ICML 2021
Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap ICML 2021
Understanding the Dynamics of Gradient Flow in Overparameterized Linear models ICML 2021
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks ICML 2021
Directional Bias Amplification ICML 2021
Quantum algorithms for reinforcement learning with a generative model ICML 2021
Thinking Like Transformers ICML 2021