Papers
Efficient Learning of Mahalanobis Metrics for Ranking
Daryl Lim, Gert Lanckriet
Doubly Stochastic Variational Bayes for non-Conjugate Inference
Michalis Titsias, Miguel Lázaro-Gredilla
Deterministic Anytime Inference for Stochastic Continuous-Time Markov Processes
E. Busra Celikkaya, Christian Shelton
Efficient Dimensionality Reduction for High-Dimensional Network Estimation
Safiye Celik, Benjamin Logsdon, Su-In Lee
Adaptive Monte Carlo via Bandit Allocation
James Neufeld, Andras Gyorgy, Csaba Szepesvari et al.
A Compilation Target for Probabilistic Programming Languages
Brooks Paige, Frank Wood
Sample-based approximate regularization
Philip Bachman, Amir-Massoud Farahmand, Doina Precup
Exponential Family Matrix Completion under Structural Constraints
Suriya Gunasekar, Pradeep Ravikumar, Joydeep Ghosh
Learning Polynomials with Neural Networks
Alexandr Andoni, Rina Panigrahy, Gregory Valiant et al.
Compositional Morphology for Word Representations and Language Modelling
Jan Botha, Phil Blunsom
Finding Dense Subgraphs via Low-Rank Bilinear Optimization
Dimitris Papailiopoulos, Ioannis Mitliagkas, Alexandros Dimakis et al.
Universal Matrix Completion
Srinadh Bhojanapalli, Prateek Jain
Estimating Latent-Variable Graphical Models using Moments and Likelihoods
Arun Tejasvi Chaganty, Percy Liang
A Clockwork RNN
Jan Koutnik, Klaus Greff, Faustino Gomez et al.
Stochastic Variational Inference for Bayesian Time Series Models
Matthew Johnson, Alan Willsky
Learning from Contagion (Without Timestamps)
Kareem Amin, Hoda Heidari, Michael Kearns
Robust Distance Metric Learning via Simultaneous L1-Norm Minimization and Maximization
Hua Wang, Feiping Nie, Heng Huang
Saddle Points and Accelerated Perceptron Algorithms
Adams Wei Yu, Fatma Kilinc-Karzan, Jaime Carbonell
Learning Character-level Representations for Part-of-Speech Tagging
Cicero Dos Santos, Bianca Zadrozny
Beta Diffusion Trees
Creighton Heaukulani, David Knowles, Zoubin Ghahramani
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors
Piyush Rai, Yingjian Wang, Shengbo Guo et al.
Neural Variational Inference and Learning in Belief Networks
Andriy Mnih, Karol Gregor
Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets
Diederik Kingma, Max Welling
Multi-period Trading Prediction Markets with Connections to Machine Learning
Jinli Hu, Amos Storkey
Towards End-To-End Speech Recognition with Recurrent Neural Networks
Alex Graves, Navdeep Jaitly