Optimization

Faster non-convex federated learning via global and local momentum UAI 2022 Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization AISTATS 2022 Faster online calibration without randomization: interval forecasts and the power of two choices COLT 2022 Faster Perturbed Stochastic Gradient Methods for Finding Local Minima ALT 2022 Faster Rates, Adaptive Algorithms, and Finite-Time Bounds for Linear Composition Optimization and Gradient TD Learning AISTATS 2022 FasterRisk: Fast and Accurate Interpretable Risk Scores NeurIPS 2022 Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity AISTATS 2022 Faster Stochastic Algorithms for Minimax Optimization under Polyak-{\L}ojasiewicz Condition NeurIPS 2022 Fast Few-shot Debugging for NLU Test Suites ACL 2022 Fast Finite Width Neural Tangent Kernel ICML 2022 Fast Fourier Transform Reductions for Bayesian Network Inference AISTATS 2022 Fast Grad-TTS: Towards Efficient Diffusion-Based Speech Generation on CPU Interspeech 2022 Fast Graph Neural Tangent Kernel via Kronecker Sketching AAAI 2022 Fast Instrument Learning with Faster Rates NeurIPS 2022 Fast Lossless Neural Compression with Integer-Only Discrete Flows ICML 2022 Fast Monte-Carlo Approximation of the Attention Mechanism AAAI 2022 Fast Population-Based Reinforcement Learning on a Single Machine ICML 2022 Fast Provably Robust Decision Trees and Boosting ICML 2022 Fast Rank-1 NMF for Missing Data with KL Divergence AISTATS 2022 Fast Regression for Structured Inputs ICLR 2022 Fast Sparse Classification for Generalized Linear and Additive Models AISTATS 2022 Fast Sparse Decision Tree Optimization via Reference Ensembles AAAI 2022 Feature and Instance Joint Selection: A Reinforcement Learning Perspective IJCAI 2022 FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning ICLR 2022 Federated Learning with Partial Model Personalization ICML 2022