36 Results

Poster
Tue 7:00 On the Global Optimality of Model-Agnostic Meta-Learning
Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Poster
Tue 7:00 LTF: A Label Transformation Framework for Correcting Label Shift
Jiaxian Guo, Mingming Gong, Tongliang Liu, Kun Zhang, Dacheng Tao
Poster
Tue 7:00 On the Generalization Effects of Linear Transformations in Data Augmentation
Sen Wu, Hongyang Zhang, Gregory Valiant, Christopher Re
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 LEEP: A New Measure to Evaluate Transferability of Learned Representations
Cuong Nguyen, Tal Hassner, Matthias W Seeger, Cedric Archambeau
Poster
Tue 7:00 Mutual Transfer Learning for Massive Data
Ching-Wei Cheng, Xingye Qiao, Guang Cheng
Poster
Tue 8:00 Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources
Yun Yun Tsai, Pin-Yu Chen, Tsung-Yi Ho
Poster
Tue 8:00 AutoML-Zero: Evolving Machine Learning Algorithms From Scratch
Esteban Real, Chen Liang, David So, Quoc Le
Poster
Tue 9:00 Stabilizing Differentiable Architecture Search via Perturbation-based Regularization
Xiangning Chen, Cho-Jui Hsieh
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 11:00 Which Tasks Should Be Learned Together in Multi-task Learning?
Trevor Standley, Amir Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, Silvio Savarese
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 13:00 Meta-learning with Stochastic Linear Bandits
Leonardo Cella, Alessandro Lazaric, Massimiliano Pontil
Poster
Tue 14:00 On the Iteration Complexity of Hypergradient Computation
Riccardo Grazzi, Luca Franceschi, Massimiliano Pontil, Saverio Salzo
Poster
Tue 15:00 Estimating Generalization under Distribution Shifts via Domain-Invariant Representations
Ching-Yao Chuang, Antonio Torralba, Stefanie Jegelka
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 9:00 Margin-aware Adversarial Domain Adaptation with Optimal Transport
Sofien Dhouib, Ievgen Redko, Carole Lartizien
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 T-GD: Transferable GAN-generated Images Detection Framework
Hyeonseong Jeon, Young Oh Bang, Junyaup Kim, Simon Woo
Poster
Thu 6:00 Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization
Deb Mahapatra, Vaibhav Rajan
Poster
Thu 6:00 Optimizing Dynamic Structures with Bayesian Generative Search
Minh Hoang, Carleton Kingsford
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 Adaptive Adversarial Multi-task Representation Learning
YUREN MAO, Weiwei Liu, Xuemin Lin
Poster
Thu 7:00 Efficient Continuous Pareto Exploration in Multi-Task Learning
Pingchuan Ma, Tao Du, Wojciech Matusik
Poster
Thu 8:00 Domain Aggregation Networks for Multi-Source Domain Adaptation
Junfeng Wen, Russell Greiner, Dale Schuurmans
Poster
Thu 9:00 Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Tim Liang, Dapeng Hu, Jiashi Feng
Poster
Thu 12:00 Learning to Rank Learning Curves
Martin Wistuba, Tejaswini Pedapati
Poster
Thu 12:00 Online Continual Learning from Imbalanced Data
Aristotelis Chrysakis, Marie-Francine Moens
Poster
Thu 13:00 Learning to Branch for Multi-Task Learning
Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
Poster
Thu 13:00 Robust Learning with the Hilbert-Schmidt Independence Criterion
Daniel Greenfeld, Uri Shalit
Poster
Thu 18:00 Few-shot Domain Adaptation by Causal Mechanism Transfer
Takeshi Teshima, Issei Sato, Masashi Sugiyama