Papers
Latent Feature Lasso
Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang et al.
Latent Intention Dialogue Models
Tsung-Hsien Wen, Yishu Miao, Phil Blunsom et al.
Latent LSTM Allocation: Joint Clustering and Non-Linear Dynamic Modeling of Sequence Data
Manzil Zaheer, Amr Ahmed, Alexander J. Smola
Latent Multi-View Subspace Clustering
Changqing Zhang, Qinghua Hu, Huazhu Fu et al.
Latent Space Embedding for Retrieval in Question-Answer Archives
Deepak P, Dinesh Garg, Shirish Shevade
Latent Variable Dialogue Models and their Diversity
Kris Cao, Stephen Clark
Lazifying Conditional Gradient Algorithms
Gábor Braun, Sebastian Pokutta, Daniel Zink
Lazy-Grounding for Answer Set Programs with External Source Access
Thomas Eiter, Tobias Kaminski, Antonius Weinzierl
LCNN: Lookup-Based Convolutional Neural Network
Hessam Bagherinezhad, Mohammad Rastegari, Ali Farhadi
LCR-Net: Localization-Classification-Regression for Human Pose
Gregory Rogez, Philippe Weinzaepfel, Cordelia Schmid
Lean Crowdsourcing: Combining Humans and Machines in an Online System
Steve Branson, Grant Van Horn, Pietro Perona
Learned Contextual Feature Reweighting for Image Geo-Localization
Hyo Jin Kim, Enrique Dunn, Jan-Michael Frahm
Learned D-AMP: Principled Neural Network based Compressive Image Recovery
Chris Metzler, Ali Mousavi, Richard Baraniuk
Learned in Translation: Contextualized Word Vectors
Bryan McCann, James Bradbury, Caiming Xiong et al.
Learned Optimizers that Scale and Generalize
Olga Wichrowska, Niru Maheswaranathan, Matthew W. Hoffman et al.
Learning Active Learning from Data
Ksenia Konyushkova, Raphael Sznitman, Pascal Fua
Learning Adaptive Receptive Fields for Deep Image Parsing Network
Zhen Wei, Yao Sun, Jinqiao Wang et al.
Learning a Deep Embedding Model for Zero-Shot Learning
Li Zhang, Tao Xiang, Shaogang Gong
Learning Affinity via Spatial Propagation Networks
Sifei Liu, Shalini De Mello, Jinwei Gu et al.
Learning a Ground Truth Ranking Using Noisy Approval Votes
Ioannis Caragiannis, Evi Micha
Learning Algorithms for Active Learning
Philip Bachman, Alessandro Sordoni, Adam Trischler
Learning a Multi-View Stereo Machine
Abhishek Kar, Christian Häne, Jitendra Malik
Learning and Applying Case Adaptation Rules for Classification: An Ensemble Approach
Vahid Jalali, David Leake, Najmeh Forouzandehmehr
Learning and Knowledge Transfer with Memory Networks for Machine Comprehension
Mohit Yadav, Lovekesh Vig, Gautam Shroff