Papers
11,015 papers found
How to Train Your MAML to Excel in Few-Shot Classification
Han-Jia Ye, Wei-Lun Chao
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
Shuai Zhang, Meng Wang, Sijia Liu et al.
How Well Does Self-Supervised Pre-Training Perform with Streaming Data?
Dapeng Hu, Shipeng Yan, Qizhengqiu Lu et al.
HTLM: Hyper-Text Pre-Training and Prompting of Language Models
Armen Aghajanyan, Dmytro Okhonko, Mike Lewis et al.
Huber Additive Models for Non-stationary Time Series Analysis
Yingjie Wang, Xianrui Zhong, Fengxiang He et al.
HyAR: Addressing Discrete-Continuous Action Reinforcement Learning via Hybrid Action Representation
Boyan Li, Hongyao Tang, YAN ZHENG et al.
Hybrid Local SGD for Federated Learning with Heterogeneous Communications
Yuanxiong Guo, Ying Sun, Rui Hu et al.
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface
Tuan Anh Le, Katherine M. Collins, Luke Hewitt et al.
Hybrid Random Features
Krzysztof Marcin Choromanski, Han Lin, Haoxian Chen et al.
HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning
Ziniu Li, Yingru Li, Yushun Zhang et al.
Hyperparameter Tuning with Renyi Differential Privacy
Nicolas Papernot, Thomas Steinke
iFlood: A Stable and Effective Regularizer
Yuexiang Xie, Zhen WANG, Yaliang Li et al.
IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenes
QI LI, Kaichun Mo, Yanchao Yang et al.
Igeood: An Information Geometry Approach to Out-of-Distribution Detection
Eduardo Dadalto Camara Gomes, Florence Alberge, Pierre Duhamel et al.
IGLU: Efficient GCN Training via Lazy Updates
S Deepak Narayanan, Aditya Sinha, Prateek Jain et al.
Illiterate DALL-E Learns to Compose
Gautam Singh, Fei Deng, Sungjin Ahn
iLQR-VAE : control-based learning of input-driven dynamics with applications to neural data
Marine Schimel, Ta-Chu Kao, Kristopher T Jensen et al.
Image BERT Pre-training with Online Tokenizer
Jinghao Zhou, Chen Wei, Huiyu Wang et al.
Imbedding Deep Neural Networks
Andrew Corbett, Dmitry Kangin
Imitation Learning by Reinforcement Learning
Kamil Ciosek
Imitation Learning from Observations under Transition Model Disparity
Tanmay Gangwani, Yuan Zhou, Jian Peng
Implicit Bias of Adversarial Training for Deep Neural Networks
Bochen Lv, Zhanxing Zhu
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks
Benjamin Bowman, Guido Montufar
Implicit Bias of Projected Subgradient Method Gives Provable Robust Recovery of Subspaces of Unknown Codimension
Paris Giampouras, Benjamin David Haeffele, Rene Vidal
Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100
Sahil Singla, Surbhi Singla, Soheil Feizi