conftrace_

convergence rate

607 papers

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Co-occurring keywords

stochastic gradient descent (1091) convex optimization (1321) stochastic optimization (1060) gradient descent (1144) convergence analysis (395) non-convex optimization (547) nonconvex optimization (316) variance reduction (523) stochastic gradient (296) learning theory (519)

Papers

Statistical Guarantees of Distributed Nearest Neighbor Classification NIPS 2020
Tight last-iterate convergence rates for no-regret learning in multi-player games NIPS 2020
Personalized Federated Learning with Moreau Envelopes NIPS 2020
Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence Rate NIPS 2020
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates NIPS 2020
Escaping the Gravitational Pull of Softmax NIPS 2020
Robustness Analysis of Non-Convex Stochastic Gradient Descent using Biased Expectations NIPS 2020
Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization ACML 2020
ODE-Inspired Analysis for the Biological Version of Oja’s Rule in Solving Streaming PCA COLT 2020
Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems COLT 2020
Finite-Time Analysis of Asynchronous Stochastic Approximation and $Q$-Learning COLT 2020
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games AISTATS 2020
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling AISTATS 2020
One Sample Stochastic Frank-Wolfe AISTATS 2020
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization AISTATS 2020
Nesterov's Acceleration for Approximate Newton JMLR 2020
Boosted Histogram Transform for Regression ICML 2020
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization ICML 2020
Closing the convergence gap of SGD without replacement ICML 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods ICML 2020
pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization IJCAI 2020
A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound AAAI 2020
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance NIPS 2020
Tight Nonparametric Convergence Rates for Stochastic Gradient Descent under the Noiseless Linear Model NIPS 2020
Towards Convergence Rate Analysis of Random Forests for Classification NIPS 2020