Papers
Inference by Learning: Speeding-up Graphical Model Optimization via a Coarse-to-Fine Cascade of Pruning Classifiers
Bruno Conejo, Nikos Komodakis, Sebastien Leprince et al.
Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit
Karin C Knudson, Jacob Yates, Alexander Huk et al.
Inferring synaptic conductances from spike trains with a biophysically inspired point process model
Kenneth W Latimer, E. J. Chichilnisky, Fred Rieke et al.
Information-based learning by agents in unbounded state spaces
Shariq A Mobin, James A Arnemann, Fritz Sommer
Iterative Neural Autoregressive Distribution Estimator NADE-k
Tapani Raiko, Yao Li, Kyunghyun Cho et al.
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation
Jonathan J Tompson, Arjun Jain, Yann LeCun et al.
Just-In-Time Learning for Fast and Flexible Inference
S. M. Ali Eslami, Daniel Tarlow, Pushmeet Kohli et al.
Kernel Mean Estimation via Spectral Filtering
Krikamol Muandet, Bharath Sriperumbudur, Bernhard Schölkopf
Large-Margin Convex Polytope Machine
Alex Kantchelian, Michael C Tschantz, Ling Huang et al.
large scale canonical correlation analysis with iterative least squares
Yichao Lu, Dean P. Foster
Large-scale L-BFGS using MapReduce
Weizhu Chen, Zhenghao Wang, Jingren Zhou
Latent Support Measure Machines for Bag-of-Words Data Classification
Yuya Yoshikawa, Tomoharu Iwata, Hiroshi Sawada
Learning a Concept Hierarchy from Multi-labeled Documents
Viet-An Nguyen, Jordan L Ying, Philip Resnik et al.
Learning Chordal Markov Networks by Dynamic Programming
Kustaa Kangas, Mikko Koivisto, Teppo Niinimäki
Learning Deep Features for Scene Recognition using Places Database
Bolei Zhou, Agata Lapedriza, Jianxiong Xiao et al.
Learning Distributed Representations for Structured Output Prediction
Vivek Srikumar, Christopher D. Manning
Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm
Jun Zhu, Junhua Mao, Alan L. Yuille
Learning Generative Models with Visual Attention
Charlie Tang, Nitish Srivastava, Ruslan Salakhutdinov
Learning Mixed Multinomial Logit Model from Ordinal Data
Sewoong Oh, Devavrat Shah
Learning Mixtures of Ranking Models
Pranjal Awasthi, Avrim Blum, Or Sheffet et al.
Learning Mixtures of Submodular Functions for Image Collection Summarization
Sebastian Tschiatschek, Rishabh K Iyer, Haochen Wei et al.
Learning Multiple Tasks in Parallel with a Shared Annotator
Haim Cohen, Koby Crammer
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics
Sergey Levine, Pieter Abbeel
Learning on graphs using Orthonormal Representation is Statistically Consistent
Rakesh Shivanna, Chiranjib Bhattacharyya