33 Results

Poster
Tue 7:00 Mutual Transfer Learning for Massive Data
Ching-Wei Cheng, Xingye Qiao, Guang Cheng
Poster
Tue 7:00 LEEP: A New Measure to Evaluate Transferability of Learned Representations
Cuong Nguyen, Tal Hassner, Matthias W Seeger, Cedric Archambeau
Poster
Tue 7:00 Searching to Exploit Memorization Effect in Learning with Noisy Labels
QUANMING YAO, Hansi Yang, Bo Han, Gang Niu, James Kwok
Poster
Tue 7:00 AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang Wang
Poster
Tue 7:00 On the Generalization Effects of Linear Transformations in Data Augmentation
Sen Wu, Hongyang Zhang, Gregory Valiant, Christopher Re
Poster
Tue 8:00 AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real, Chen Liang, David So, Quoc Le
Poster
Tue 8:00 Meta-learning for Mixed Linear Regression
Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh
Poster
Tue 8:00 NADS: Neural Architecture Distribution Search for Uncertainty Awareness
Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian
Poster
Tue 9:00 Stabilizing Differentiable Architecture Search via Perturbation-based Regularization
Xiangning Chen, Cho-Jui Hsieh
Poster
Tue 10:00 A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
Nikunj Saunshi, Yi Zhang, Misha Khodak, Sanjeev Arora
Poster
Tue 10:00 Learning To Stop While Learning To Predict
Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
Poster
Tue 10:00 Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
Felipe Petroski Such, Aditya Rawal, Joel Lehman, Ken Stanley, Jeffrey Clune
Poster
Tue 12:00 TaskNorm: Rethinking Batch Normalization for Meta-Learning
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E Turner
Poster
Tue 12:00 Meta-Learning with Shared Amortized Variational Inference
Ekaterina Iakovleva, Jakob Verbeek, Karteek Alahari
Poster
Tue 14:00 On the Iteration Complexity of Hypergradient Computation
Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo
Poster
Tue 18:00 Learning to Learn Kernels with Variational Random Features
Xiantong Zhen, Haoliang Sun, Yingjun Du, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek
Poster
Wed 5:00 The Differentiable Cross-Entropy Method
Brandon Amos, Denis Yarats
Poster
Wed 8:00 Frustratingly Simple Few-Shot Object Detection
Xin Wang, Thomas Huang, Joseph E Gonzalez, Prof. Darrell, Fisher Yu
Poster
Wed 13:00 Fast Adaptation to New Environments via Policy-Dynamics Value Functions
Roberta Raileanu, Max Goldstein, Arthur Szlam, Facebook Rob Fergus
Poster
Wed 13:00 Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location
Rasheed El-Bouri, David Eyre, Peter Watkinson, Tingting Zhu, David Clifton
Poster
Wed 13:00 Super-efficiency of automatic differentiation for functions defined as a minimum
Pierre Ablin, Gabriel Peyré, Thomas Moreau
Poster
Wed 15:00 XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
Sung Whan Yoon, Do-Yeon Kim, Jun Seo, Jaekyun Moon
Poster
Wed 15:00 MetaFun: Meta-Learning with Iterative Functional Updates
Jin Xu, Jean-Francois Ton, Hyunjik Kim, Adam Kosiorek, Yee-Whye Teh
Poster
Wed 16:00 Automated Synthetic-to-Real Generalization
Wuyang Chen, Zhiding Yu, Zhangyang Wang, Anima Anandkumar
Poster
Thu 6:00 Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks
Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein
Poster
Thu 6:00 Meta Variance Transfer: Learning to Augment from the Others
Seong-Jin Park, Seungju Han, Ji-won Baek, Insoo Kim, Juhwan Song, Hae Beom Lee, Jae-Joon Han, Sung Ju Hwang
Poster
Thu 6:00 Optimizing Dynamic Structures with Bayesian Generative Search
Minh Hoang, Carleton Kingsford
Poster
Thu 6:00 Robustifying Sequential Neural Processes
Jaesik Yoon, Gautam Singh, Sungjin Ahn
Poster
Thu 8:00 Few-shot Relation Extraction via Bayesian Meta-learning on Relation Graphs
Meng Qu, Tianyu Gao, Louis-Pascal Xhonneux, Jian Tang
Poster
Thu 12:00 Learning to Rank Learning Curves
Martin Wistuba, Tejaswini Pedapati
Poster
Thu 12:00 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
Poster
Thu 13:00 Learning to Branch for Multi-Task Learning
Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
Poster
Thu 13:00 A quantile-based approach for hyperparameter transfer learning
David Salinas, Huibin Shen, Valerio Perrone