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Stochastic Methods

2788 directly classified papers

Papers per year

Papers

Learning to Bootstrap for Entity Set Expansion EMNLP 2019
Stochastic Goal Recognition Design AAAI 2019
Thompson Sampling Guided Stochastic Searching on the Line for Deceptive Environments with Applications to Root-Finding Problems JMLR 2019
Communication-Efficient Stochastic Gradient MCMC for Neural Networks AAAI 2019
Proximal Splitting Meets Variance Reduction AISTATS 2019
Towards Gradient Free and Projection Free Stochastic Optimization AISTATS 2019
Open Problem: Do Good Algorithms Necessarily Query Bad Points? COLT 2019
Accelerated Incremental Gradient Descent using Momentum Acceleration with Scaling Factor IJCAI 2019
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points NIPS 2019
Space lower bounds for linear prediction in the streaming model COLT 2019
Fast determinantal point processes via distortion-free intermediate sampling COLT 2019
Space and Time Efficient Kernel Density Estimation in High Dimensions NIPS 2019
Shenango: Achieving High CPU Efficiency for Latency-sensitive Datacenter Workloads NSDI 2019
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization IJCAI 2019
Estimating the Mixing Time of Ergodic Markov Chains COLT 2019
Highly Parallelized Data-Driven MPC for Minimal Intervention Shared Control RSS 2019
SGD: General Analysis and Improved Rates ICML 2019
SAGA with Arbitrary Sampling ICML 2019
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning ICML 2019
Principal Component Projection and Regression in Nearly Linear Time through Asymmetric SVRG NIPS 2019
Hiring Under Uncertainty ICML 2019
Beyond Gradient Descent for Regularized Segmentation Losses CVPR 2019
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization ICML 2019
Regret Bounds for Thompson Sampling in Episodic Restless Bandit Problems NIPS 2019
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits ICML 2019