Papers
Selective Sampling with Drift
Edward Moroshko, Koby Crammer
On the Testability of Models with Missing Data
Karthika Mohan, Judea Pearl
A Geometric Algorithm for Scalable Multiple Kernel Learning
John Moeller, Parasaran Raman, Suresh Venkatasubramanian et al.
Efficient Lifting of MAP LP Relaxations Using k-Locality
Martin Mladenov, Kristian Kersting, Amir Globerson
Interpretable Sparse High-Order Boltzmann Machines
Martin Renqiang Min, Xia Ning, Chao Cheng et al.
Active Boundary Annotation using Random MAP Perturbations
Subhransu Maji, Tamir Hazan, Tommi Jaakkola
Active Area Search via Bayesian Quadrature
Yifei Ma, Roman Garnett, Jeff Schneider
PAC-Bayesian Collective Stability
Ben London, Bert Huang, Ben Taskar et al.
Learning Heterogeneous Hidden Markov Random Fields
Jie Liu, Chunming Zhang, Elizabeth Burnside et al.
Jointly Informative Feature Selection
Leonidas Lefakis, Francois Fleuret
Incremental Tree-Based Inference with Dependent Normalized Random Measures
Juho Lee, Seungjin Choi
Towards building a Crowd-Sourced Sky Map
Dustin Lang, David Hogg, Bernhard Schölkopf
Computational Education using Latent Structured Prediction
Tanja Käser, Alexander Schwing, Tamir Hazan et al.
Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data
Abhimanu Kumar, Alex Beutel, Qirong Ho et al.
Low-Rank Spectral Learning
Alex Kulesza, N. Raj Rao, Satinder Singh
Visual Boundary Prediction: A Deep Neural Prediction Network and Quality Dissection
Jyri Kivinen, Chris Williams, Nicolas Heess
Algebraic Reconstruction Bounds and Explicit Inversion for Phase Retrieval at the Identifiability Threshold
Franz Király, Martin Ehler
Scalable Variational Bayesian Matrix Factorization with Side Information
Yong-Deok Kim, Seungjin Choi
A Gaussian Latent Variable Model for Large Margin Classification of Labeled and Unlabeled Data
Do-kyum Kim, Matthew Der, Lawrence Saul
Scalable Collaborative Bayesian Preference Learning
Mohammad Emtiyaz Khan, Young Jun Ko, Matthias Seeger
Collaborative Ranking for Local Preferences
Berk Kapicioglu, David Rosenberg, Robert Schapire et al.
Recovering Distributions from Gaussian RKHS Embeddings
Motonobu Kanagawa, Kenji Fukumizu
A Level-set Hit-and-run Sampler for Quasi-Concave Distributions
Shane Jensen, Dean Foster
Near Optimal Bayesian Active Learning for Decision Making
Shervin Javdani, Yuxin Chen, Amin Karbasi et al.