Papers
11,015 papers found
Learning to cluster in order to transfer across domains and tasks
Yen-Chang Hsu, Zhaoyang Lv, Zsolt Kira
Learning to Count Objects in Natural Images for Visual Question Answering
Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
Learning to Multi-Task by Active Sampling
Sahil Sharma*, Ashutosh Kumar Jha*, Parikshit S Hegde et al.
Learning to Represent Programs with Graphs
Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi
LEARNING TO SHARE: SIMULTANEOUS PARAMETER TYING AND SPARSIFICATION IN DEEP LEARNING
Dejiao Zhang, Haozhu Wang, Mario Figueiredo et al.
Learning to Teach
Yang Fan, Fei Tian, Tao Qin et al.
Learning Wasserstein Embeddings
Nicolas Courty, Rémi Flamary, Mélanie Ducoffe
Learn to Pay Attention
Saumya Jetley, Nicholas A. Lord, Namhoon Lee et al.
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning
Benjamin Eysenbach, Shixiang Gu, Julian Ibarz et al.
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis
Rudy Bunel, Matthew Hausknecht, Jacob Devlin et al.
Lifelong Learning with Dynamically Expandable Networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee et al.
Loss-aware Weight Quantization of Deep Networks
Lu Hou, James T. Kwok
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
William Fedus*, Mihaela Rosca*, Balaji Lakshminarayanan et al.
MaskGAN: Better Text Generation via Filling in the _______
William Fedus, Ian Goodfellow, Andrew M. Dai
Mastering the Dungeon: Grounded Language Learning by Mechanical Turker Descent
Zhilin Yang, Saizheng Zhang, Jack Urbanek et al.
Matrix capsules with EM routing
Geoffrey E Hinton, Sara Sabour, Nicholas Frosst
Maximum a Posteriori Policy Optimisation
Abbas Abdolmaleki, Jost Tobias Springenberg, Yuval Tassa et al.
Measuring the Intrinsic Dimension of Objective Landscapes
Chunyuan Li, Heerad Farkhoor, Rosanne Liu et al.
Memorization Precedes Generation: Learning Unsupervised GANs with Memory Networks
Youngjin Kim, Minjung Kim, Gunhee Kim
Memory Architectures in Recurrent Neural Network Language Models
Dani Yogatama, Yishu Miao, Gabor Melis et al.
Memory Augmented Control Networks
Arbaaz Khan, Clark Zhang, Nikolay Atanasov et al.
Memory-based Parameter Adaptation
Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae et al.
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm
Chelsea Finn, Sergey Levine
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren, Eleni Triantafillou, Sachin Ravi et al.
META LEARNING SHARED HIERARCHIES
Kevin Frans, Jonathan Ho, Xi Chen et al.