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Few-Shot Learning via Learning the Representation, Provably

21 February 2020

Papers citing "Few-Shot Learning via Learning the Representation, Provably"

49 / 99 papers shown

Title
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects Tobias Hatt Jeroen Berrevoets Alicia Curth Stefan Feuerriegel M. Schaar CML 90 32 0 25 Feb 2022
Sample Efficiency of Data Augmentation Consistency Regularization Shuo Yang Yijun Dong Rachel A. Ward Inderjit S. Dhillon Sujay Sanghavi Qi Lei AAML 84 17 0 24 Feb 2022
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution Ananya Kumar Aditi Raghunathan Robbie Jones Tengyu Ma Percy Liang OODD 142 687 0 21 Feb 2022
Adaptive and Robust Multi-Task Learning Yaqi Duan Kaizheng Wang 130 27 0 10 Feb 2022
Learning Mixtures of Linear Dynamical Systems Yanxi Chen H. Vincent Poor 113 17 0 26 Jan 2022
Variational Model Inversion Attacks Kuan-Chieh Wang Yanzhe Fu Ke Li Ashish Khisti R. Zemel Alireza Makhzani MIACV 94 98 0 26 Jan 2022
Towards Sample-efficient Overparameterized Meta-learning Yue Sun Adhyyan Narang Halil Ibrahim Gulluk Samet Oymak Maryam Fazel BDL 60 25 0 16 Jan 2022
Non-Stationary Representation Learning in Sequential Linear Bandits Yuzhen Qin Tommaso Menara Samet Oymak ShiNung Ching Fabio Pasqualetti OffRL 78 17 0 13 Jan 2022
Joint Learning-Based Stabilization of Multiple Unknown Linear Systems Mohamad Kazem Shirani Faradonbeh Aditya Modi 88 6 0 01 Jan 2022
On the Role of Neural Collapse in Transfer Learning Tomer Galanti András Gyorgy Marcus Hutter SSL 88 93 0 30 Dec 2021
Joint Learning of Linear Time-Invariant Dynamical Systems Aditya Modi Mohamad Kazem Shirani Faradonbeh Ambuj Tewari George Michailidis 135 17 0 21 Dec 2021
On the Statistical Benefits of Curriculum Learning Ziping Xu Ambuj Tewari 56 9 0 13 Nov 2021
Scaffolding Sets M. Burhanpurkar Zhun Deng Cynthia Dwork Linjun Zhang 83 9 0 04 Nov 2021
Provable Lifelong Learning of Representations Xinyuan Cao Weiyang Liu Santosh Vempala CLL 71 16 0 27 Oct 2021
A Closer Look at Prototype Classifier for Few-shot Image Classification Mingcheng Hou Issei Sato VLM 103 21 0 11 Oct 2021
The Power of Contrast for Feature Learning: A Theoretical Analysis Wenlong Ji Zhun Deng Ryumei Nakada James Zou Linjun Zhang SSL 134 53 0 06 Oct 2021
A Scaling Law for Synthetic-to-Real Transfer: How Much Is Your Pre-training Effective? Hiroaki Mikami Kenji Fukumizu Shogo Murai Shuji Suzuki Yuta Kikuchi Taiji Suzuki S. Maeda Kohei Hayashi 92 12 0 25 Aug 2021
Going Beyond Linear RL: Sample Efficient Neural Function Approximation Baihe Huang Kaixuan Huang Sham Kakade Jason D. Lee Qi Lei Runzhe Wang Jiaqi Yang 101 8 0 14 Jul 2021
MAML is a Noisy Contrastive Learner in Classification Chia-Hsiang Kao Wei-Chen Chiu Pin-Yu Chen 37 17 0 29 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng Linjun Zhang Kailas Vodrahalli Kenji Kawaguchi James Zou GAN 89 54 0 18 Jun 2021
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation Haoxiang Wang Han Zhao Yue Liu 112 90 0 16 Jun 2021
On the Power of Multitask Representation Learning in Linear MDP Rui Lu Gao Huang S. Du 83 29 0 15 Jun 2021
Meta-Adaptive Nonlinear Control: Theory and Algorithms Guanya Shi Kamyar Azizzadenesheli Michael O'Connell Soon-Jo Chung Yisong Yue 113 41 0 11 Jun 2021
Probing transfer learning with a model of synthetic correlated datasets Federica Gerace Luca Saglietti Stefano Sarao Mannelli Andrew M. Saxe Lenka Zdeborová OOD 56 32 0 09 Jun 2021
What Makes Multi-modal Learning Better than Single (Provably) Yu Huang Chenzhuang Du Zihui Xue Xuanyao Chen Hang Zhao Longbo Huang 100 268 0 08 Jun 2021
Model Zoo: A Growing "Brain" That Learns Continually Rahul Ramesh Pratik Chaudhari CLL FedML 111 66 0 06 Jun 2021
Meta-Learning with Fewer Tasks through Task Interpolation Huaxiu Yao Linjun Zhang Chelsea Finn 114 56 0 04 Jun 2021
Representation Learning Beyond Linear Prediction Functions Ziping Xu Ambuj Tewari 67 21 0 31 May 2021
Weighted Training for Cross-Task Learning Shuxiao Chen K. Crammer Han He Dan Roth Weijie J. Su 83 28 0 28 May 2021
How Fine-Tuning Allows for Effective Meta-Learning Kurtland Chua Qi Lei Jason D. Lee 95 50 0 05 May 2021
How to distribute data across tasks for meta-learning? Alexandru Cioba Michael Bromberg Qian Wang R. Niyogi Georgios Batzolis Jezabel R. Garcia Da-shan Shiu A. Bernacchia FedML 53 8 0 15 Mar 2021
For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions Nishanth Dikkala Gal Kaplun Rina Panigrahy 56 7 0 11 Mar 2021
Meta-Learning with Graph Neural Networks: Methods and Applications Debmalya Mandal Sourav Medya Brian Uzzi Charu C. Aggarwal AI4CE 106 22 0 27 Feb 2021
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution Amrith Rajagopal Setlur Oscar Li Virginia Smith 161 13 0 23 Feb 2021
Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning Halil Ibrahim Gulluk Yue Sun Samet Oymak Maryam Fazel 60 2 0 14 Feb 2021
Exploiting Shared Representations for Personalized Federated Learning Liam Collins Hamed Hassani Aryan Mokhtari Sanjay Shakkottai FedML OOD 105 736 0 14 Feb 2021
Near-optimal Representation Learning for Linear Bandits and Linear RL Jiachen Hu Xiaoyu Chen Chi Jin Lihong Li Liwei Wang OffRL 165 53 0 08 Feb 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 159 173 0 15 Dec 2020
Invariant Feature Learning for Sensor-based Human Activity Recognition Yujiao Hao Boyu Wang Rong Zheng 81 20 0 14 Dec 2020
A Distribution-Dependent Analysis of Meta-Learning Mikhail Konobeev Ilja Kuzborskij Csaba Szepesvári OOD 71 5 0 31 Oct 2020
Theoretical bounds on estimation error for meta-learning James Lucas Mengye Ren Irene Kameni T. Pitassi R. Zemel 51 12 0 14 Oct 2020
Impact of Representation Learning in Linear Bandits Jiaqi Yang Wei Hu Jason D. Lee S. Du 97 53 0 13 Oct 2020
How Important is the Train-Validation Split in Meta-Learning? Yu Bai Minshuo Chen Pan Zhou T. Zhao Jason D. Lee Sham Kakade Haiquan Wang Caiming Xiong 96 53 0 12 Oct 2020
Improving Few-Shot Learning through Multi-task Representation Learning Theory Quentin Bouniot I. Redko Romaric Audigier Angélique Loesch Amaury Habrard 103 10 0 05 Oct 2020
Predicting What You Already Know Helps: Provable Self-Supervised Learning Jason D. Lee Qi Lei Nikunj Saunshi Jiacheng Zhuo SSL 109 190 0 03 Aug 2020
The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks Wei Hu Lechao Xiao Ben Adlam Jeffrey Pennington 72 63 0 25 Jun 2020
Generalisation Guarantees for Continual Learning with Orthogonal Gradient Descent Mehdi Abbana Bennani Thang Doan Masashi Sugiyama CLL 132 65 0 21 Jun 2020
On the Theory of Transfer Learning: The Importance of Task Diversity Nilesh Tripuraneni Michael I. Jordan Chi Jin 138 221 0 20 Jun 2020
Understanding and Improving Information Transfer in Multi-Task Learning Sen Wu Hongyang R. Zhang Christopher Ré 69 158 0 02 May 2020