Statistical Learning
Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
We consider nonconvex stochastic optimization problems in the asynchronous centralized distributed setup where the communication times from workers to a server can not be ignored, and the computation and communication times are potentially different for all workers.
Learning A Structured Optimal Bipartite Graph for Co-Clustering
Feiping Nie, Xiaoqian Wang, Cheng Deng, Heng Huang
Ingraph based co-clustering methods, abipartite graph isconstructed todepict the relation between features and samples.
On model selection consistency of penalized M-estimators: a geometric theory
Jason D. Lee, Yuekai Sun, Jonathan E. Taylor
Neural Information Processing Systems http://nips.cc/
Conditional Generative Moment-Matching Networks
Yong Ren, Jun Zhu, Jialian Li, Yucen Luo
Neural Information Processing Systems http://nips.cc/
Online Bayesian Moment Matching for Topic Modeling with Unknown Number of Topics
Neural Information Processing Systems http://nips.cc/
A fast, universal algorithm to learn parametric nonlinear embeddings
Miguel A. Carreira-Perpinan, Max Vladymyrov
Using the method of auxiliary coordinates, we derive a training algorithm that works by alternating steps that train an auxiliary embeddingwith steps that train the mapping.