convex function

Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training ICML 2025 Revisiting Differentially Private Algorithms for Decentralized Online Learning ICML 2025 Chasing Convex Functions with Long-term Constraints ICML 2024 Generalized Preference Optimization: A Unified Approach to Offline Alignment ICML 2024 Generalized Sobolev Transport for Probability Measures on a Graph ICML 2024 Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm ICML 2024 Omnipredictors for regression and the approximate rank of convex functions COLT 2024 On a Neural Implementation of Brenier’s Polar Factorization ICML 2024 Difference of submodular minimization via DC programming ICML 2023 Stochastic Optimization under Distributional Drift JMLR 2023 Faster Algorithms for Learning Convex Functions ICML 2022 First-Order Convex Fitting and Its Application to Economics and Optimization AAAI 2022 When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint JMLR 2022 Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees NeurIPS 2021 Optimal transport mapping via input convex neural networks ICML 2020 Artificial Constraints and Hints for Unbounded Online Learning COLT 2019 Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron AISTATS 2019 Sample Efficient Graph-Based Optimization with Noisy Observations AISTATS 2019 Efficient Convex Optimization with Membership Oracles COLT 2018 Randomized Block Cubic Newton Method ICML 2018 Input Convex Neural Networks ICML 2017 Sparse Accelerated Exponential Weights AISTATS 2017 Algorithms and matching lower bounds for approximately-convex optimization NeurIPS 2016 Multi-scale exploration of convex functions and bandit convex optimization COLT 2016 On the Influence of Momentum Acceleration on Online Learning JMLR 2016