Papers
Activized Learning with Uniform Classification Noise
Liu Yang, Steve Hanneke
Adaptive Hamiltonian and Riemann Manifold Monte Carlo
Ziyu Wang, Shakir Mohamed, Nando Freitas
Adaptive Sparsity in Gaussian Graphical Models
Eleanor Wong, Suyash Awate, P. Thomas Fletcher
Adaptive Task Assignment for Crowdsourced Classification
Chien-Ju Ho, Shahin Jabbari, Jennifer Wortman Vaughan
A Fast and Exact Energy Minimization Algorithm for Cycle MRFs
Huayan Wang, Koller Daphne
A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems
Pinghua Gong, Changshui Zhang, Zhaosong Lu et al.
A Generalized Kernel Approach to Structured Output Learning
Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux
Algorithms for Direct 0–1 Loss Optimization in Binary Classification
Tan Nguyen, Scott Sanner
Almost Optimal Exploration in Multi-Armed Bandits
Zohar Karnin, Tomer Koren, Oren Somekh
A Local Algorithm for Finding Well-Connected Clusters
Zeyuan Allen Zhu, Silvio Lattanzi, Vahab Mirrokni
A Machine Learning Framework for Programming by Example
Aditya Menon, Omer Tamuz, Sumit Gulwani et al.
An Adaptive Learning Rate for Stochastic Variational Inference
Rajesh Ranganath, Chong Wang, Blei David et al.
Analogy-preserving Semantic Embedding for Visual Object Categorization
Sung Ju Hwang, Kristen Grauman, Fei Sha
An Efficient Posterior Regularized Latent Variable Model for Interactive Sound Source Separation
Nicholas Bryan, Gautham Mysore
A non-IID Framework for Collaborative Filtering with Restricted Boltzmann Machines
Kostadin Georgiev, Preslav Nakov
An Optimal Policy for Target Localization with Application to Electron Microscopy
Raphael Sznitman, Aurelien Lucchi, Peter Frazier et al.
Anytime Representation Learning
Zhixiang Xu, Matt Kusner, Gao Huang et al.
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers
Pascal Germain, Amaury Habrard, François Laviolette et al.
Approximate Inference in Collective Graphical Models
Daniel Sheldon, Tao Sun, Akshat Kumar et al.
Approximation properties of DBNs with binary hidden units and real-valued visible units
Oswin Krause, Asja Fischer, Tobias Glasmachers et al.
A Practical Algorithm for Topic Modeling with Provable Guarantees
Sanjeev Arora, Rong Ge, Yonatan Halpern et al.
A proximal Newton framework for composite minimization: Graph learning without Cholesky decompositions and matrix inversions
Quoc Tran Dinh, Anastasios Kyrillidis, Volkan Cevher
A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning
Arash Afkanpour, András György, Csaba Szepesvari et al.