Statistical Learning
Enhancing the Accuracy and Fairness of Human Decision Making
Isabel Valera, Adish Singla, Manuel Gomez Rodriguez
However, these decisions may be imperfect due to limited experience, implicit biases, or faulty probabilistic reasoning.
A Dual Framework for Low-rank Tensor Completion
Madhav Nimishakavi, Pratik Kumar Jawanpuria, Bamdev Mishra
We develop a dual framework for solving the low-rank tensor completion problem.
MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization
Ian En-Hsu Yen, Wei-Cheng Lee, Kai Zhong, Sung-En Chang, Pradeep K. Ravikumar, Shou-De Lin
We consider a generalization of mixed regression where the response is an additive combination of several mixture components.
Distributed Weight Consolidation: A Brain Segmentation Case Study
Patrick McClure, Charles Y. Zheng, Jakub Kaczmarzyk, John Rogers-Lee, Satra Ghosh, Dylan Nielson, Peter A. Bandettini, Francisco Pereira
Neural Information Processing Systems http://nips.cc/
Contextual Stochastic Block Models
Yash Deshpande, Subhabrata Sen, Andrea Montanari, Elchanan Mossel
Data clustering is a widely used primitive in exploratory data analysis and summarization.
Interactive Structure Learning with Structural Query-by-Committee
Christopher Tosh, Sanjoy Dasgupta
We present a generalization of the query-by-committee active learning algorithm for this setting, and we study its consistency and rate of convergence, both theoretically and empirically, with and without noise.
Learning Plannable Representations with Causal InfoGAN
Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart J. Russell, Pieter Abbeel
In recent years, deep generative models have been shown to'imagine' convincing
Stochastic Primal-Dual Method for Empirical Risk Minimization with O(1) Per-Iteration Complexity
Conghui Tan, Tong Zhang, Shiqian Ma, Ji Liu
Neural Information Processing Systems http://nips.cc/
Query K-means Clustering and the Double Dixie Cup Problem
I Chien, Chao Pan, Olgica Milenkovic
Among the state-of-the-art K-means approximation methods are the algorithms of Kanungo et al. and Ahmadian et al [