Papers
Efficient Lifting of MAP LP Relaxations Using k-Locality
Martin Mladenov, Kristian Kersting, Amir Globerson
Efficient Low-Rank Stochastic Gradient Descent Methods for Solving Semidefinite Programs
Jianhui Chen, Tianbao Yang, Shenghuo Zhu
Efficiently Enforcing Diversity in Multi-Output Structured Prediction
Abner Guzman-Rivera, Pushmeet Kohli, Dhruv Batra et al.
Efficient Transfer Learning Method for Automatic Hyperparameter Tuning
Dani Yogatama, Gideon Mann
Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations
Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno et al.
Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables
Tomi Peltola, Pasi Jylänki, Aki Vehtari
Explicit Link Between Periodic Covariance Functions and State Space Models
Arno Solin, Simo Särkkä
Exploiting the Limits of Structure Learning via Inherent Symmetry
Peng He, Changshui Zhang
Fast Distribution To Real Regression
Junier Oliva, Willie Neiswanger, Barnabas Poczos et al.
Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data
Abhimanu Kumar, Alex Beutel, Qirong Ho et al.
Fully-Automatic Bayesian Piecewise Sparse Linear Models
Riki Eto, Ryohei Fujimaki, Satoshi Morinaga et al.
FuSSO: Functional Shrinkage and Selection Operator
Junier Oliva, Barnabas Poczos, Timothy Verstynen et al.
Gaussian Copula Precision Estimation with Missing Values
Huahua Wang, Farideh Fazayeli, Soumyadeep Chatterjee et al.
Generating Efficient MCMC Kernels from Probabilistic Programs
Lingfeng Yang, Patrick Hanrahan, Noah Goodman
Global Optimization Methods for Extended Fisher Discriminant Analysis
Satoru Iwata, Yuji Nakatsukasa, Akiko Takeda
Heterogeneous Domain Adaptation for Multiple Classes
Joey Tianyi Zhou, Ivor W.Tsang, Sinno Jialin Pan et al.
High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation
Rafael Izbicki, Ann Lee, Chad Schafer
Hybrid Discriminative-Generative Approach with Gaussian Processes
Ricardo Andrade Pacheco, James Hensman, Max Zwiessele et al.
Incremental Tree-Based Inference with Dependent Normalized Random Measures
Juho Lee, Seungjin Choi
In Defense of Minhash over Simhash
Anshumali Shrivastava, Ping Li
Information-Theoretic Characterization of Sparse Recovery
Cem Aksoylar, Venkatesh Saligrama
Interpretable Sparse High-Order Boltzmann Machines
Martin Renqiang Min, Xia Ning, Chao Cheng et al.
Jointly Informative Feature Selection
Leonidas Lefakis, Francois Fleuret
Joint Structure Learning of Multiple Non-Exchangeable Networks
Chris Oates, Sach Mukherjee