Papers
Fast Prediction for Large-Scale Kernel Machines
Cho-Jui Hsieh, Si Si, Inderjit S Dhillon
Sparse Multi-Task Reinforcement Learning
Daniele Calandriello, Alessandro Lazaric, Marcello Restelli
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors
Lingqiao Liu, Chunhua Shen, Lei Wang et al.
Multi-Scale Spectral Decomposition of Massive Graphs
Si Si, Donghyuk Shin, Inderjit S Dhillon et al.
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models
Yarin Gal, Mark van der Wilk, Carl Edward Rasmussen
A statistical model for tensor PCA
Emile Richard, Andrea Montanari
A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance Estimation
Eran Treister, Javier S Turek
Deep Recursive Neural Networks for Compositionality in Language
Ozan Irsoy, Claire Cardie
On the Convergence Rate of Decomposable Submodular Function Minimization
Robert Nishihara, Stefanie Jegelka, Michael I Jordan
Local Decorrelation For Improved Pedestrian Detection
Woonhyun Nam, Piotr Dollar, Joon Hee Han
Consistency of Spectral Partitioning of Uniform Hypergraphs under Planted Partition Model
Debarghya Ghoshdastidar, Ambedkar Dukkipati
Two-Stream Convolutional Networks for Action Recognition in Videos
Karen Simonyan, Andrew Zisserman
Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)
Anshumali Shrivastava, Ping Li
Learning with Fredholm Kernels
Qichao Que, Mikhail Belkin, Yusu Wang
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics
Sergey Levine, Pieter Abbeel
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights
Daniel Soudry, Itay Hubara, Ron Meir
Positive Curvature and Hamiltonian Monte Carlo
Christof Seiler, Simon Rubinstein-Salzedo, Susan Holmes
Scalable Kernel Methods via Doubly Stochastic Gradients
Bo Dai, Bo Xie, Niao He et al.
A Probabilistic Framework for Multimodal Retrieval using Integrative Indian Buffet Process
Bahadir Ozdemir, Larry S. Davis
The limits of squared Euclidean distance regularization
Michal Derezinski, Manfred K. Warmuth
A Filtering Approach to Stochastic Variational Inference
Neil Houlsby, David Blei
Sparse Bayesian structure learning with “dependent relevance determination” priors
Anqi Wu, Mijung Park, Oluwasanmi O Koyejo et al.
Streaming, Memory Limited Algorithms for Community Detection
Se-Young Yun, marc lelarge, Alexandre Proutiere
Extremal Mechanisms for Local Differential Privacy
Peter Kairouz, Sewoong Oh, Pramod Viswanath