Papers
Using Trajectory Data to Improve Bayesian Optimization for Reinforcement Learning
Aaron Wilson, Alan Fern, Prasad Tadepalli
Convex vs Non-Convex Estimators for Regression and Sparse Estimation: the Mean Squared Error Properties of ARD and GLasso
Aleksandr Aravkin, James V. Burke, Alessandro Chiuso et al.
Axioms for Graph Clustering Quality Functions
Twan van Laarhoven, Elena Marchiori
A Junction Tree Framework for Undirected Graphical Model Selection
Divyanshu Vats, Robert D. Nowak
EnsembleSVM: A Library for Ensemble Learning Using Support Vector Machines
Marc Claesen, Frank De Smet, Johan A.K. Suykens et al.
Detecting Click Fraud in Online Advertising: A Data Mining Approach
Richard Oentaryo, Ee-Peng Lim, Michael Finegold et al.
Fast SVM Training Using Approximate Extreme Points
Manu Nandan, Pramod P. Khargonekar, Sachin S. Talathi
Bridging Viterbi and Posterior Decoding: A Generalized Risk Approach to Hidden Path Inference Based on Hidden Markov Models
Jüri Lember, Alexey A. Koloydenko
Influence Function Learning in Information Diffusion Networks
Nan Du, Yingyu Liang, Maria Balcan et al.
Structured Low-Rank Matrix Factorization: Optimality, Algorithm, and Applications to Image Processing
Benjamin Haeffele, Eric Young, Rene Vidal
A reversible infinite HMM using normalised random measures
David Knowles, Zoubin Ghahramani, Konstantina Palla
GEV-Canonical Regression for Accurate Binary Class Probability Estimation when One Class is Rare
Arpit Agarwal, Harikrishna Narasimhan, Shivaram Kalyanakrishnan et al.
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