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ORCIDIEEE Journal on Selected Areas in Information Theory, Volume 5
Volume 5, 2024
- Venugopal V. Veeravalli
, Georgios Fellouris, George V. Moustakides:
Quickest Change Detection With Controlled Sensing. 1-11 - Antonious M. Girgis, Suhas N. Diggavi:
Multi-Message Shuffled Privacy in Federated Learning. 12-27 - Anand Jerry George, Lekshmi Ramesh, Aditya Vikram Singh, Himanshu Tyagi:
Continual Mean Estimation Under User-Level Privacy. 28-43 - Matteo Zecchin, Sangwoo Park, Osvaldo Simeone:
Forking Uncertainties: Reliable Prediction and Model Predictive Control With Sequence Models via Conformal Risk Control. 44-61 - Chen Xu, Jonghyeok Lee, Xiuyuan Cheng, Yao Xie:
Flow-Based Distributionally Robust Optimization. 62-77 - Zirui Yan, Arpan Mukherjee, Burak Varici, Ali Tajer:
Robust Causal Bandits for Linear Models. 78-93 - Ruida Zhou, Chao Tian, Tie Liu:
Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem. 94-104 - Alireza Sadeghi, Gang Wang, Georgios B. Giannakis:
Learning Robust to Distributional Uncertainties and Adversarial Data. 105-122 - Hyun-Young Park, Seung-Hyun Nam, Si-Hyeon Lee:
Exactly Optimal and Communication-Efficient Private Estimation via Block Designs. 123-134 - Osama A. Hanna, Antonious M. Girgis, Christina Fragouli, Suhas N. Diggavi:
Differentially Private Stochastic Linear Bandits: (Almost) for Free. 135-147 - Neophytos Charalambides, Hessam Mahdavifar, Mert Pilanci, Alfred O. Hero III:
Iterative Sketching for Secure Coded Regression. 148-161 - Sahel Torkamani, Javad B. Ebrahimi, Parastoo Sadeghi, Rafael G. L. D'Oliveira, Muriel Médard:
Optimal Binary Differential Privacy via Graphs. 162-174 - Xinying Zou, Samir M. Perlaza, Iñaki Esnaola, Eitan Altman, H. Vincent Poor:
The Worst-Case Data-Generating Probability Measure in Statistical Learning. 175-189 - Songtao Feng, Ming Yin, Ruiquan Huang, Yu-Xiang Wang, Jing Yang, Yingbin Liang:
Toward General Function Approximation in Nonstationary Reinforcement Learning. 190-206 - Elena Ghazi, Ibrahim Issa:
Total Variation Meets Differential Privacy. 207-220 - Daria Reshetova, Wei-Ning Chen, Ayfer Özgür:
Training Generative Models From Privatized Data via Entropic Optimal Transport. 221-235 - Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi:
Improving Group Testing via Gradient Descent. 236-245 - Ezgi Özyilkan, Johannes Ballé, Elza Erkip:
Neural Distributed Compressor Discovers Binning. 246-260 - Mark Beliaev, Payam Delgosha, Hamed Hassani, Ramtin Pedarsani:
Efficient and Robust Classification for Sparse Attacks. 261-272 - Gholamali Aminian, Mohammad Saeed Masiha, Laura Toni, Miguel R. D. Rodrigues:
Learning Algorithm Generalization Error Bounds via Auxiliary Distributions. 273-284 - Baturalp Buyukates, Jinhyun So, Hessam Mahdavifar, Salman Avestimehr:
LightVeriFL: A Lightweight and Verifiable Secure Aggregation for Federated Learning. 285-301 - Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
Noisy Computing of the OR and MAX Functions. 302-313 - Giuseppe Serra, Photios A. Stavrou, Marios Kountouris:
On the Computation of the Gaussian Rate-Distortion-Perception Function. 314-330 - Mohamed Seif, Yanxi Chen, Andrea J. Goldsmith, H. Vincent Poor:
Differentially Private Sketch-and-Solve for Community Detection via Semidefinite Programming. 331-346 - Zinan Lin, Shuaiqi Wang, Vyas Sekar, Giulia Fanti:
Summary Statistic Privacy in Data Sharing. 369-384 - Ruizhi Zhang:
Detection of Sparse Mixtures With Differential Privacy. 347-356 - Faisal Hamman, Erfaun Noorani, Saumitra Mishra, Daniele Magazzeni, Sanghamitra Dutta:
Robust Algorithmic Recourse Under Model Multiplicity With Probabilistic Guarantees. 357-368 - Shahab Asoodeh, Huanyu Zhang:
Contraction of Locally Differentially Private Mechanisms. 385-395 - Yauhen Yakimenka, Chung-Wei Weng, Hsuan-Yin Lin, Eirik Rosnes, Jörg Kliewer:
Straggler-Resilient Differentially Private Decentralized Learning. 407-423 - Xinyi Tong, Jian Xu, Shao-Lun Huang:
On the Fundamental Limit of Distributed Learning With Interchangable Constrained Statistics. 396-406 - Bhagyashree Puranik, Ozgur Guldogan, Upamanyu Madhow, Ramtin Pedarsani:
Long-Term Fairness in Sequential Multi-Agent Selection With Positive Reinforcement. 424-441 - Shahrzad Kiani, Franziska Boenisch, Stark C. Draper:
Controlled Privacy Leakage Propagation Throughout Overlapping Grouped Learning. 442-463 - Hassan ZivariFard, Rémi A. Chou:
Secure Source Coding Resilient Against Compromised Users via an Access Structure. 478-492 - Jay Whang, Alliot Nagle, Anish Acharya, Hyeji Kim, Alexandros G. Dimakis:
Neural Distributed Source Coding. 493-508 - Ariel K. Feldman, Praveen Venkatesh, Douglas J. Weber, Pulkit Grover:
Information-Theoretic Tools to Understand Distributed Source Coding in Neuroscience. 509-519 - Yanyan Dong, Shenghao Yang, Jie Wang, Fan Cheng:
Throughput and Latency Analysis for Line Networks With Outage Links. 464-477 - Ahmed H. Salamah, Kaixiang Zheng, Linfeng Ye, En-Hui Yang:
JPEG Compliant Compression for DNN Vision. 520-533 - Monica Welfert, Gowtham R. Kurri, Kyle Otstot, Lalitha Sankar:
Addressing GAN Training Instabilities via Tunable Classification Losses. 534-553 - Elad Domanovitz, Anatoly Khina, Tal Philosof, Yuval Kochman:
Information Velocity of Cascaded Gaussian Channels With Feedback. 554-569 - Baturalp Buyukates, Jinhyun So, Hessam Mahdavifar, Salman Avestimehr:
Erratum to "LightVeriFL: A Lightweight and Verifiable Secure Aggregation for Federated Learning". 570-571 - Nadim Ghaddar, Lele Wang:
Low-Complexity Coding Techniques for Cloud Radio Access Networks. 572-584 - Ruze Zhang, Xuan Guang, Shenghao Yang, Xueyan Niu, Bo Bai:
Computation of Binary Arithmetic Sum Over an Asymmetric Diamond Network. 585-596
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last updated on 2024-10-02 20:44 CEST by the dblp team
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