Papers
How They Vote: Issue-Adjusted Models of Legislative Behavior
Sean Gerrish, David M. Blei
Nonconvex Penalization Using Laplace Exponents and Concave Conjugates
Zhihua Zhang, Bojun Tu
A Divide-and-Conquer Method for Sparse Inverse Covariance Estimation
Cho-jui Hsieh, Arindam Banerjee, Inderjit S. Dhillon et al.
Convergence and Energy Landscape for Cheeger Cut Clustering
Xavier Bresson, Thomas Laurent, David Uminsky et al.
A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes
Thomas Furmston, David Barber
Multi-Task Averaging
Sergey Feldman, Maya Gupta, Bela Frigyik
Kernel Hyperalignment
Alexander Lorbert, Peter J. Ramadge
A Bayesian Approach for Policy Learning from Trajectory Preference Queries
Aaron Wilson, Alan Fern, Prasad Tadepalli
Discriminatively Trained Sparse Code Gradients for Contour Detection
Ren Xiaofeng, Liefeng Bo
The Perturbed Variation
Maayan Harel, Shie Mannor
A Spectral Algorithm for Latent Dirichlet Allocation
Anima Anandkumar, Dean P. Foster, Daniel J. Hsu et al.
Multi-criteria Anomaly Detection using Pareto Depth Analysis
Ko-jen Hsiao, Kevin Xu, Jeff Calder et al.
Human memory search as a random walk in a semantic network
Joseph L. Austerweil, Joshua T. Abbott, Thomas L. Griffiths
Nonparametric Bayesian Inverse Reinforcement Learning for Multiple Reward Functions
Jaedeug Choi, Kee-eung Kim
Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints
Stefan Habenschuss, Johannes Bill, Bernhard Nessler
Deep Learning of Invariant Features via Simulated Fixations in Video
Will Zou, Shenghuo Zhu, Kai Yu et al.
Distributed Non-Stochastic Experts
Varun Kanade, Zhenming Liu, Bozidar Radunovic
On Multilabel Classification and Ranking with Partial Feedback
Claudio Gentile, Francesco Orabona
Learning Invariant Representations of Molecules for Atomization Energy Prediction
Grégoire Montavon, Katja Hansen, Siamac Fazli et al.
Convex Multi-view Subspace Learning
Martha White, Xinhua Zhang, Dale Schuurmans et al.
Learning Mixtures of Tree Graphical Models
Anima Anandkumar, Daniel J. Hsu, Furong Huang et al.
Searching for objects driven by context
Bogdan Alexe, Nicolas Heess, Yee W. Teh et al.
Graphical Models via Generalized Linear Models
Eunho Yang, Genevera Allen, Zhandong Liu et al.
Learning visual motion in recurrent neural networks
Marius Pachitariu, Maneesh Sahani
Proximal Newton-type methods for convex optimization
Jason Lee, Yuekai Sun, Michael Saunders