convergence guarantee

Training Neural Networks Using Features Replay NeurIPS 2018 An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis ICML 2017 Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent NeurIPS 2017 Neural Taylor Approximations: Convergence and Exploration in Rectifier Networks ICML 2017 Sub-sampled Cubic Regularization for Non-convex Optimization ICML 2017 A ranking approach to global optimization ICML 2016 Provably manipulation-resistant reputation systems COLT 2016 Scalable Adaptive Stochastic Optimization Using Random Projections NeurIPS 2016 Beyond Convexity: Stochastic Quasi-Convex Optimization NeurIPS 2015 Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015 Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees NeurIPS 2015 On Convergence of Emphatic Temporal-Difference Learning COLT 2015 A Geometric Algorithm for Scalable Multiple Kernel Learning AISTATS 2014 Bias in Natural Actor-Critic Algorithms ICML 2014 Communication Efficient Distributed Machine Learning with the Parameter Server NeurIPS 2014 Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion NeurIPS 2014 Least Squares Revisited: Scalable Approaches for Multi-class Prediction ICML 2014 More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server NeurIPS 2013 Better Mini-Batch Algorithms via Accelerated Gradient Methods NeurIPS 2011 Convergent Fitted Value Iteration with Linear Function Approximation NeurIPS 2011 Speedy Q-Learning NeurIPS 2011 The Fixed Points of Off-Policy TD NeurIPS 2011