Papers
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity
Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
Learning with SGD and Random Features
Luigi Carratino, Alessandro Rudi, Lorenzo Rosasco
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy, Matan Haroush, Nadav Merlis et al.
Legendre Decomposition for Tensors
Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
Leveraged volume sampling for linear regression
Michal Derezinski, Manfred K. Warmuth, Daniel J. Hsu
Leveraging the Exact Likelihood of Deep Latent Variable Models
Pierre-Alexandre Mattei, Jes Frellsen
LF-Net: Learning Local Features from Images
Yuki Ono, Eduard Trulls, Pascal Fua et al.
Life-Long Disentangled Representation Learning with Cross-Domain Latent Homologies
Alessandro Achille, Tom Eccles, Loic Matthey et al.
Lifelong Inverse Reinforcement Learning
Jorge Mendez, Shashank Shivkumar, Eric Eaton
Lifted Weighted Mini-Bucket
Nicholas Gallo, Alex Ihler
Limited Memory Kelley's Method Converges for Composite Convex and Submodular Objectives
Song Zhou, Swati Gupta, Madeleine Udell
LinkNet: Relational Embedding for Scene Graph
Sanghyun Woo, Dahun Kim, Donghyeon Cho et al.
Link Prediction Based on Graph Neural Networks
Muhan Zhang, Yixin Chen
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks
Yusuke Tsuzuku, Issei Sato, Masashi Sugiyama
Lipschitz regularity of deep neural networks: analysis and efficient estimation
Aladin Virmaux, Kevin Scaman
Local Differential Privacy for Evolving Data
Matthew Joseph, Aaron Roth, Jonathan Ullman et al.
Long short-term memory and Learning-to-learn in networks of spiking neurons
Guillaume Bellec, Darjan Salaj, Anand Subramoney et al.
Loss Functions for Multiset Prediction
Sean Welleck, Zixin Yao, Yu Gai et al.
Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs
Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin et al.
Low-rank Interaction with Sparse Additive Effects Model for Large Data Frames
Geneviève Robin, Hoi-To Wai, Julie Josse et al.
Low-Rank Tucker Decomposition of Large Tensors Using TensorSketch
Osman Asif Malik, Stephen Becker
Low-shot Learning via Covariance-Preserving Adversarial Augmentation Networks
Hang Gao, Zheng Shou, Alireza Zareian et al.
MacNet: Transferring Knowledge from Machine Comprehension to Sequence-to-Sequence Models
Boyuan Pan, Yazheng Yang, Hao Li et al.
Mallows Models for Top-k Lists
Flavio Chierichetti, Anirban Dasgupta, Shahrzad Haddadan et al.
Manifold Structured Prediction
Alessandro Rudi, Carlo Ciliberto, GianMaria Marconi et al.