Optimization

Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases AISTATS 2024 Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements AISTATS 2024 Symbolic Cognitive Diagnosis via Hybrid Optimization for Intelligent Education Systems AAAI 2024 Symbolic Regression with a Learned Concept Library NeurIPS 2024 Symmetry-Informed Governing Equation Discovery NeurIPS 2024 Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve OSDI 2024 The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks NeurIPS 2024 The Fine-Grained Complexity of Gradient Computation for Training Large Language Models NeurIPS 2024 The Sample Complexity of Gradient Descent in Stochastic Convex Optimization NeurIPS 2024 The Space Complexity of Approximating Logistic Loss NeurIPS 2024 Tight Convergence Rate Bounds for Optimization Under Power Law Spectral Conditions JMLR 2024 Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective NeurIPS 2024 Time-Constrained Robust MDPs NeurIPS 2024 Towards Scalable and Stable Parallelization of Nonlinear RNNs NeurIPS 2024 Trace is the Next AutoDiff: Generative Optimization with Rich Feedback, Execution Traces, and LLMs NeurIPS 2024 Training-Free Quantum Architecture Search AAAI 2024 Two-timescale Extragradient for Finding Local Minimax Points ICLR 2024 Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization ICLR 2024 Unit Selection with Nonbinary Treatment and Effect AAAI 2024 Win: Weight-Decay-Integrated Nesterov Acceleration for Faster Network Training JMLR 2024 A Case of Exponential Convergence Rates for SVM AISTATS 2023 Accelerated and Sparse Algorithms for Approximate Personalized PageRank and Beyond COLT 2023 Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization ICML 2023 Accelerated Infeasibility Detection of Constrained Optimization and Fixed-Point Iterations ICML 2023 Accelerated Single-Call Methods for Constrained Min-Max Optimization ICLR 2023