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• DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy

  Anda Cheng, Jiaxing Wang, Xi Sheryl Zhang, Qiang Chen, Peisong Wang, Jian Cheng

  6358-6366

  2022-06-28

• Graph Neural Controlled Differential Equations for Traffic Forecasting

  Jeongwhan Choi, Hwangyong Choi, Jeehyun Hwang, Noseong Park

  6367-6374

  2022-06-28

• Differentially Private Regret Minimization in Episodic Markov Decision Processes

  Sayak Ray Chowdhury, Xingyu Zhou

  6375-6383

  2022-06-28

• Learning by Competition of Self-Interested Reinforcement Learning Agents

  Stephen Chung

  6384-6393

  2022-06-28

• How to Distribute Data across Tasks for Meta-Learning?

  Alexandru Cioba, Michael Bromberg, Qian Wang, Ritwik Niyogi, Georgios Batzolis, Jezabel Garcia, Da-shan Shiu, Alberto Bernacchia

  6394-6401

  2022-06-28

• Similarity Search for Efficient Active Learning and Search of Rare Concepts

  Cody Coleman, Edward Chou, Julian Katz-Samuels, Sean Culatana, Peter Bailis, Alexander C. Berg, Robert Nowak, Roshan Sumbaly, Matei Zaharia, I. Zeki Yalniz

  6402-6410

  2022-06-28

• Learning Influence Adoption in Heterogeneous Networks

  Vincent Conitzer, Debmalya Panigrahi, Hanrui Zhang

  6411-6419

  2022-06-28

• Graph-Wise Common Latent Factor Extraction for Unsupervised Graph Representation Learning

  Thilini Cooray, Ngai-Man Cheung

  6420-6428

  2022-06-28

• Reinforcement Learning with Stochastic Reward Machines

  Jan Corazza, Ivan Gavran, Daniel Neider

  6429-6436

  2022-06-28

• Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks

  Francesco Croce, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, Matthias Hein

  6437-6445

  2022-06-28

• Learning Logic Programs Though Divide, Constrain, and Conquer

  Andrew Cropper

  6446-6453

  2022-06-28

• Implicit Gradient Alignment in Distributed and Federated Learning

  Yatin Dandi, Luis Barba, Martin Jaggi

  6454-6462

  2022-06-28

• How Good Are Low-Rank Approximations in Gaussian Process Regression?

  Constantinos Daskalakis, Petros Dellaportas, Aristeidis Panos

  6463-6470

  2022-06-28

• KOALA: A Kalman Optimization Algorithm with Loss Adaptivity

  Aram Davtyan, Sepehr Sameni, Llukman Cerkezi, Givi Meishvili, Adam Bielski, Paolo Favaro

  6471-6479

  2022-06-28

• First-Order Convex Fitting and Its Application to Economics and Optimization

  Quinlan Dawkins, Minbiao Han, Haifeng Xu

  6480-6487

  2022-06-28

• Gradient Temporal Difference with Momentum: Stability and Convergence

  Rohan Deb, Shalabh Bhatnagar

  6488-6496

  2022-06-28

• Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes

  Florent Delgrange, Ann Nowé, Guillermo A. Pérez

  6497-6505

  2022-06-28

• Reducing Flipping Errors in Deep Neural Networks

  Xiang Deng, Yun Xiao, Bo Long, Zhongfei Zhang

  6506-6514

  2022-06-28

• Bayesian Optimization over Permutation Spaces

  Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa, Dae Hyun Kim

  6515-6523

  2022-06-28

• Meta Propagation Networks for Graph Few-shot Semi-supervised Learning

  Kaize Ding, Jianling Wang, James Caverlee, Huan Liu

  6524-6531

  2022-06-28

• Online Certification of Preference-Based Fairness for Personalized Recommender Systems

  Virginie Do, Sam Corbett-Davies, Jamal Atif, Nicolas Usunier

  6532-6540

  2022-06-28

• Disentangled Spatiotemporal Graph Generative Models

  Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao

  6541-6549

  2022-06-28

• Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples

  Wei Duan, Junyu Xuan, Maoying Qiao, Jie Lu

  6550-6558

  2022-06-28

• Adaptive and Universal Algorithms for Variational Inequalities with Optimal Convergence

  Alina Ene, Huy Lê Nguyễn

  6559-6567

  2022-06-28

• Zero-Shot Out-of-Distribution Detection Based on the Pre-trained Model CLIP

  Sepideh Esmaeilpour, Bing Liu, Eric Robertson, Lei Shu

  6568-6576

  2022-06-28