Papers
Active Learning for Multi-Objective Optimization
Marcela Zuluaga, Guillaume Sergent, Andreas Krause et al.
Scaling Multidimensional Gaussian Processes using Projected Additive Approximations
Elad Gilboa, Yunus Saatçi, John Cunningham et al.
Iterative Learning and Denoising in Convolutional Neural Associative Memories
Amin Karbasi, Amir Hesam Salavati, Amin Shokrollahi
General Functional Matrix Factorization Using Gradient Boosting
Tianqi Chen, Hang Li, Qiang Yang et al.
Approximation properties of DBNs with binary hidden units and real-valued visible units
Oswin Krause, Asja Fischer, Tobias Glasmachers et al.
Learning with Marginalized Corrupted Features
Laurens Maaten, Minmin Chen, Stephen Tyree et al.
Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery
Yudong Chen, Constantine Caramanis
A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning
Arash Afkanpour, András György, Csaba Szepesvari et al.
Optimal rates for stochastic convex optimization under Tsybakov noise condition
Aaditya Ramdas, Aarti Singh
Parsing epileptic events using a Markov switching process model for correlated time series
Drausin Wulsin, Emily Fox, Brian Litt
Efficient Dimensionality Reduction for Canonical Correlation Analysis
Haim Avron, Christos Boutsidis, Sivan Toledo et al.
Human Boosting
Harsh Pareek, Pradeep Ravikumar
Feature Selection in High-Dimensional Classification
Mladen Kolar, Han Liu
Average Reward Optimization Objective In Partially Observable Domains
Yuri Grinberg, Doina Precup
Adaptive Sparsity in Gaussian Graphical Models
Eleanor Wong, Suyash Awate, P. Thomas Fletcher
Maximum Variance Correction with Application to A* Search
Wenlin Chen, Kilian Weinberger, Yixin Chen
Efficient Sparse Group Feature Selection via Nonconvex Optimization
Shuo Xiang, Xiaoshen Tong, Jieping Ye
Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks
Creighton Heaukulani, Zoubin Ghahramani
Learning Optimally Sparse Support Vector Machines
Andrew Cotter, Shai Shalev-Shwartz, Nati Srebro
Multiple Identifications in Multi-Armed Bandits
Séebastian Bubeck, Tengyao Wang, Nitin Viswanathan
Learning Linear Bayesian Networks with Latent Variables
Animashree Anandkumar, Daniel Hsu, Adel Javanmard et al.