Statistical Learning
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates
Kirill Struminsky, Simon Lacoste-Julien, Anton Osokin
Neural Information Processing Systems http://nips.cc/
Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes
This paper studies statistical characteristics of multivariate observations with irregular changes in their covariance structures across input space.
DropMax: Adaptive Variational Softmax
Hae Beom Lee, Juho Lee, Saehoon Kim, Eunho Yang, Sung Ju Hwang
Neural Information Processing Systems http://nips.cc/
Guided Similarity Separation for Image Retrieval
Chundi Liu, Guangwei Yu, Maksims Volkovs, Cheng Chang, Himanshu Rai, Junwei Ma, Satya Krishna Gorti
Neural Information Processing Systems http://nips.cc/
PAC-Bayes bounds for stable algorithms with instance-dependent priors
Omar Rivasplata, Csaba Szepesvari, John S. Shawe-Taylor, Emilio Parrado-Hernandez, Shiliang Sun
Neural Information Processing Systems http://nips.cc/
Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates
Krishnakumar Balasubramanian, Saeed Ghadimi
Neural Information Processing Systems http://nips.cc/
NearNeighbor
We show that LSH based algorithms can be made fair, without a significant loss in efficiency. Specifically, we show an algorithm that reports a point in the rneighborhood of a query q with almost uniform probability.