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2020 – today
- 2023
[j28]Mohammad Vahid Jamali
, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes. IEEE J. Sel. Areas Inf. Theory 4: 260-275 (2023)- [c85]Zheng Xu, Maxwell D. Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan:
Learning to Generate Image Embeddings with User-Level Differential Privacy. CVPR 2023: 7969-7980 - [c84]Jonathan Hayase, Sewoong Oh:
Few-shot Backdoor Attacks via Neural Tangent Kernels. ICLR 2023 - [c83]Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Guha Thakurta, Lun Wang:
Why Is Public Pretraining Necessary for Private Model Training? ICML 2023: 10611-10627 - [c82]S. Ashwin Hebbar, Viraj Vivek Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath:
CRISP: Curriculum based Sequential neural decoders for Polar code family. ICML 2023: 12823-12845 - [c81]Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh:
Private Federated Learning with Autotuned Compression. ICML 2023: 34668-34708 - [i92]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes. CoRR abs/2301.06251 (2023) - [i91]Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala:
Near Optimal Private and Robust Linear Regression. CoRR abs/2301.13273 (2023) - [i90]Galen Andrew, Peter Kairouz, Sewoong Oh, Alina Oprea, H. Brendan McMahan, Vinith Suriyakumar:
One-shot Empirical Privacy Estimation for Federated Learning. CoRR abs/2302.03098 (2023) - [i89]Arun Ganesh, Mahdi Haghifam, Milad Nasr, Sewoong Oh, Thomas Steinke, Om Thakkar, Abhradeep Thakurta, Lun Wang:
Why Is Public Pretraining Necessary for Private Model Training? CoRR abs/2302.09483 (2023) - [i88]Arun Ganesh, Daogao Liu, Sewoong Oh, Abhradeep Thakurta:
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks. CoRR abs/2302.09699 (2023) - [i87]Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang:
Challenges towards the Next Frontier in Privacy. CoRR abs/2304.06929 (2023) - [i86]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - [i85]Boxin Wang, Jacky Yibo Zhang, Yuan Cao, Bo Li, H. Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer:
Can Public Large Language Models Help Private Cross-device Federated Learning? CoRR abs/2305.12132 (2023) - [i84]Krishna Pillutla, Galen Andrew, Peter Kairouz, H. Brendan McMahan, Alina Oprea, Sewoong Oh:
Unleashing the Power of Randomization in Auditing Differentially Private ML. CoRR abs/2305.18447 (2023) - [i83]Thao Nguyen, Samir Yitzhak Gadre, Gabriel Ilharco, Sewoong Oh, Ludwig Schmidt:
Improving Multimodal Datasets with Image Captioning. CoRR abs/2307.10350 (2023) - [i82]Enayat Ullah, Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh:
Private Federated Learning with Autotuned Compression. CoRR abs/2307.10999 (2023) - [i81]Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ludwig Schmidt, Ali Farhadi:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. CoRR abs/2307.12532 (2023) - 2022
- [c80]Kiran Koshy Thekumparampil, Niao He, Sewoong Oh:
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization. AISTATS 2022: 4281-4308 - [c79]Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying:
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC 2022: 16-25 - [c78]Xiyang Liu, Weihao Kong, Sewoong Oh:
Differential privacy and robust statistics in high dimensions. COLT 2022: 1167-1246 - [c77]Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning. ICLR 2022 - [c76]Xingyu Wang, Sewoong Oh, Chang-Han Rhee:
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise. ICLR 2022 - [c75]Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai:
MAML and ANIL Provably Learn Representations. ICML 2022: 4238-4310 - [c74]Melih Yilmaz, William Fondrie, Wout Bittremieux, Sewoong Oh, William S. Noble:
De novo mass spectrometry peptide sequencing with a transformer model. ICML 2022: 25514-25522 - [c73]Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. NeurIPS 2022 - [c72]Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh:
DP-PCA: Statistically Optimal and Differentially Private PCA. NeurIPS 2022 - [c71]Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt:
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. NeurIPS 2022 - [c70]Liang Zhang, Kiran K. Thekumparampil, Sewoong Oh, Niao He:
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization. NeurIPS 2022 - [i80]Kiran Koshy Thekumparampil, Niao He, Sewoong Oh:
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization. CoRR abs/2201.07427 (2022) - [i79]Liam Collins, Aryan Mokhtari, Sewoong Oh, Sanjay Shakkottai:
MAML and ANIL Provably Learn Representations. CoRR abs/2202.03483 (2022) - [i78]Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh:
Towards a Defense against Backdoor Attacks in Continual Federated Learning. CoRR abs/2205.11736 (2022) - [i77]Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh:
DP-PCA: Statistically Optimal and Differentially Private PCA. CoRR abs/2205.13709 (2022) - [i76]Liang Zhang, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He:
Bring Your Own Algorithm for Optimal Differentially Private Stochastic Minimax Optimization. CoRR abs/2206.00363 (2022) - [i75]Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt:
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP. CoRR abs/2208.05516 (2022) - [i74]S. Ashwin Hebbar, Viraj Nadkarni, Ashok Vardhan Makkuva, Suma Bhat, Sewoong Oh, Pramod Viswanath:
CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family. CoRR abs/2210.00313 (2022) - [i73]Zaïd Harchaoui, Sewoong Oh, Soumik Pal, Raghav Somani, Raghavendra Tripathi:
Stochastic optimization on matrices and a graphon McKean-Vlasov limit. CoRR abs/2210.00422 (2022) - [i72]Jonathan Hayase, Sewoong Oh:
Few-shot Backdoor Attacks via Neural Tangent Kernels. CoRR abs/2210.05929 (2022) - [i71]Matt Jordan, Jonathan Hayase, Alexandros G. Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. CoRR abs/2210.08069 (2022) - [i70]Zheng Xu, Maxwell D. Collins, Yuxiao Wang, Liviu Panait, Sewoong Oh, Sean Augenstein, Ting Liu, Florian Schroff, H. Brendan McMahan:
Learning to Generate Image Embeddings with User-level Differential Privacy. CoRR abs/2211.10844 (2022) - [i69]Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
MAUVE Scores for Generative Models: Theory and Practice. CoRR abs/2212.14578 (2022) - 2021
- [c69]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
Defense against backdoor attacks via robust covariance estimation. ICML 2021: 4129-4139 - [c68]Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning. ICML 2021: 7368-7378 - [c67]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding. ISIT 2021: 1088-1093 - [c66]Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh:
Robust and differentially private mean estimation. NeurIPS 2021: 3887-3901 - [c65]Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. NeurIPS 2021: 12930-12942 - [c64]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Statistically and Computationally Efficient Linear Meta-representation Learning. NeurIPS 2021: 18487-18500 - [c63]Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok:
Gradient Inversion with Generative Image Prior. NeurIPS 2021: 29898-29908 - [i68]Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding. CoRR abs/2102.01671 (2021) - [i67]Xingyu Wang, Sewoong Oh, Chang-Han Rhee:
Eliminating Sharp Minima from SGD with Truncated Heavy-tailed Noise. CoRR abs/2102.04297 (2021) - [i66]Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
Efficient Algorithms for Federated Saddle Point Optimization. CoRR abs/2102.06333 (2021) - [i65]Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh:
Robust and Differentially Private Mean Estimation. CoRR abs/2102.09159 (2021) - [i64]Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh:
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. CoRR abs/2104.11315 (2021) - [i63]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Sample Efficient Linear Meta-Learning by Alternating Minimization. CoRR abs/2105.08306 (2021) - [i62]Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral. CoRR abs/2106.07898 (2021) - [i61]Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
Reducing the Communication Cost of Federated Learning through Multistage Optimization. CoRR abs/2108.06869 (2021) - [i60]Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath:
KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-learning. CoRR abs/2108.12920 (2021) - [i59]Jinwoo Jeon, Jaechang Kim, Kangwook Lee, Sewoong Oh, Jungseul Ok:
Gradient Inversion with Generative Image Prior. CoRR abs/2110.14962 (2021) - [i58]Xiyang Liu, Weihao Kong, Sewoong Oh:
Differential privacy and robust statistics in high dimensions. CoRR abs/2111.06578 (2021) - [i57]Sewoong Oh, Soumik Pal, Raghav Somani, Raghav Tripathi:
Gradient flows on graphons: existence, convergence, continuity equations. CoRR abs/2111.09459 (2021) - 2020
- [j27]Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett:
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1(1): 4 (2020) - [j26]Hyeji Kim, Sewoong Oh, Pramod Viswanath:
Physical Layer Communication via Deep Learning. IEEE J. Sel. Areas Inf. Theory 1(1): 5-18 (2020) - [j25]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode: Feedback Codes via Deep Learning. IEEE J. Sel. Areas Inf. Theory 1(1): 194-206 (2020) - [j24]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks. IEEE J. Sel. Areas Inf. Theory 1(1): 207-216 (2020) - [j23]Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh:
PacGAN: The Power of Two Samples in Generative Adversarial Networks. IEEE J. Sel. Areas Inf. Theory 1(1): 324-335 (2020) - [j22]Weizhao Tang, Weina Wang, Giulia Fanti, Sewoong Oh:
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks. Proc. ACM Meas. Anal. Comput. Syst. 4(2): 29:1-29:39 (2020) - [c62]Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Learning in Gated Neural Networks. AISTATS 2020: 3338-3348 - [c61]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Feedback Turbo Autoencoder. ICASSP 2020: 8559-8563 - [c60]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for Mixed Linear Regression. ICML 2020: 5394-5404 - [c59]Zinan Lin, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs. ICML 2020: 6127-6139 - [c58]Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee:
Optimal transport mapping via input convex neural networks. ICML 2020: 6672-6681 - [c57]Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh:
Robust Meta-learning for Mixed Linear Regression with Small Batches. NeurIPS 2020 - [c56]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method. NeurIPS 2020 - [c55]Weizhao Tang, Weina Wang, Giulia Fanti, Sewoong Oh:
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks. SIGMETRICS (Abstracts) 2020: 81-82 - [c54]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Joint Channel Coding and Modulation via Deep Learning. SPAWC 2020: 1-5 - [i56]Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh:
Meta-learning for mixed linear regression. CoRR abs/2002.08936 (2020) - [i55]Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh:
Robust Meta-learning for Mixed Linear Regression with Small Batches. CoRR abs/2006.09702 (2020) - [i54]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode and Modulo-SK are Designed for Different Settings. CoRR abs/2008.07997 (2020) - [i53]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Projection Efficient Subgradient Method and Optimal Nonsmooth Frank-Wolfe Method. CoRR abs/2010.01848 (2020)
2010 – 2019
- 2019
- [j21]Ashish Khetan, Sewoong Oh:
Spectrum Estimation from a Few Entries. J. Mach. Learn. Res. 20: 21:1-21:55 (2019) - [c53]Jungseul Ok, Sewoong Oh, Yunhun Jang, Jinwoo Shin, Yung Yi:
Iterative Bayesian Learning for Crowdsourced Regression. AISTATS 2019: 1486-1495 - [c52]Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath:
Learning One-hidden-layer Neural Networks under General Input Distributions. AISTATS 2019: 1950-1959 - [c51]Giulia Fanti, Leonid Kogan, Sewoong Oh, Kathleen Ruan, Pramod Viswanath, Gerui Wang:
Compounding of Wealth in Proof-of-Stake Cryptocurrencies. Financial Cryptography 2019: 42-61 - [c50]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks. ICC 2019: 1-7 - [c49]Weihao Gao, Yu-Han Liu, Chong Wang, Sewoong Oh:
Rate Distortion For Model Compression: From Theory To Practice. ICML 2019: 2102-2111 - [c48]Ashok Vardhan Makkuva, Pramod Viswanath, Sreeram Kannan, Sewoong Oh:
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms. ICML 2019: 4304-4313 - [c47]Giulia Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath:
Barracuda: The Power of ℓ-polling in Proof-of-Stake Blockchains. MobiHoc 2019: 351-360 - [c46]Xiyang Liu, Sewoong Oh:
Minimax Optimal Estimation of Approximate Differential Privacy on Neighboring Databases. NeurIPS 2019: 2414-2425 - [c45]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels. NeurIPS 2019: 2754-2764 - [c44]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Efficient Algorithms for Smooth Minimax Optimization. NeurIPS 2019: 12659-12670 - [c43]Yihan Jiang, Sreeram Kannan, Hyeji Kim, Sewoong Oh, Himanshu Asnani, Pramod Viswanath:
DEEPTURBO: Deep Turbo Decoder. SPAWC 2019: 1-5 - [i52]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
DeepTurbo: Deep Turbo Decoder. CoRR abs/1903.02295 (2019) - [i51]Xiyang Liu, Sewoong Oh:
Minimax Rates of Estimating Approximate Differential Privacy. CoRR abs/1905.10335 (2019) - [i50]Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath:
Learning in Gated Neural Networks. CoRR abs/1906.02777 (2019) - [i49]Kiran Koshy Thekumparampil, Sewoong Oh, Ashish Khetan:
Robust conditional GANs under missing or uncertain labels. CoRR abs/1906.03579 (2019) - [i48]Zinan Lin, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh:
InfoGAN-CR: Disentangling Generative Adversarial Networks with Contrastive Regularizers. CoRR abs/1906.06034 (2019) - [i47]Kiran Koshy Thekumparampil, Prateek Jain, Praneeth Netrapalli, Sewoong Oh:
Efficient Algorithms for Smooth Minimax Optimization. CoRR abs/1907.01543 (2019) - [i46]Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee:
Optimal transport mapping via input convex neural networks. CoRR abs/1908.10962 (2019) - [i45]Weizhao Tang, Weina Wang, Giulia Fanti, Sewoong Oh:
Privacy-Utility Tradeoffs in Routing Cryptocurrency over Payment Channel Networks. CoRR abs/1909.02717 (2019) - [i44]Giulia Fanti, Jiantao Jiao, Ashok Vardhan Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath:
Barracuda: The Power of 𝓁-polling in Proof-of-Stake Blockchains. CoRR abs/1909.08719 (2019) - [i43]Xuechao Wang, Govinda M. Kamath, Vivek Kumar Bagaria, Sreeram Kannan, Sewoong Oh, David Tse, Pramod Viswanath:
Proof-of-Stake Longest Chain Protocols Revisited. CoRR abs/1910.02218 (2019) - [i42]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels. CoRR abs/1911.03038 (2019) - 2018
- [j20]Ashish Khetan, Sewoong Oh:
Generalized Rank-Breaking: Computational and Statistical Tradeoffs. J. Mach. Learn. Res. 19: 28:1-28:42 (2018) - [j19]Sahand Negahban, Sewoong Oh, Kiran Koshy Thekumparampil, Jiaming Xu:
Learning from Comparisons and Choices. J. Mach. Learn. Res. 19: 40:1-40:95 (2018) - [j18]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation. IEEE Trans. Inf. Theory 64(5): 3313-3330 (2018) - [j17]Weihao Gao, Sewoong Oh, Pramod Viswanath:
Demystifying Fixed k-Nearest Neighbor Information Estimators. IEEE Trans. Inf. Theory 64(8): 5629-5661 (2018) - [j16]Jungseul Ok, Sewoong Oh, Jinwoo Shin, Yung Yi:
Optimal Inference in Crowdsourced Classification via Belief Propagation. IEEE Trans. Inf. Theory 64(9): 6127-6138 (2018) - [c42]Hyeji Kim, Yihan Jiang, Ranvir Rana, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Communication Algorithms via Deep Learning. ICLR (Poster) 2018 - [c41]Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh:
PacGAN: The power of two samples in generative adversarial networks. NeurIPS 2018: 1505-1514 - [c40]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode: Feedback Codes via Deep Learning. NeurIPS 2018: 9458-9468 - [c39]Kiran Koshy Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh:
Robustness of conditional GANs to noisy labels. NeurIPS 2018: 10292-10303 - [i41]Kiran Koshy Thekumparampil, Chong Wang, Sewoong Oh, Li-Jia Li:
Attention-based Graph Neural Network for Semi-supervised Learning. CoRR abs/1803.03735 (2018) - [i40]Hyeji Kim, Yihan Jiang, Ranvir Rana, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Communication Algorithms via Deep Learning. CoRR abs/1805.09317 (2018) - [i39]Hyeji Kim, Yihan Jiang, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Deepcode: Feedback Codes via Deep Learning. CoRR abs/1807.00801 (2018) - [i38]Giulia Fanti, Leonid Kogan, Sewoong Oh, Kathleen Ruan, Pramod Viswanath, Gerui Wang:
Compounding of Wealth in Proof-of-Stake Cryptocurrencies. CoRR abs/1809.07468 (2018) - [i37]Weihao Gao, Ashok Vardhan Makkuva, Sewoong Oh, Pramod Viswanath:
Learning One-hidden-layer Neural Networks under General Input Distributions. CoRR abs/1810.04133 (2018) - [i36]Weihao Gao, Chong Wang, Sewoong Oh:
Rate Distortion For Model Compression: From Theory To Practice. CoRR abs/1810.06401 (2018) - [i35]Kiran Koshy Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh:
Robustness of Conditional GANs to Noisy Labels. CoRR abs/1811.03205 (2018) - [i34]Yihan Jiang, Hyeji Kim, Himanshu Asnani, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
LEARN Codes: Inventing Low-latency Codes via Recurrent Neural Networks. CoRR abs/1811.12707 (2018) - [i33]Ashish Khetan, Harshay Shah, Sewoong Oh:
Number of Connected Components in a Graph: Estimation via Counting Patterns. CoRR abs/1812.00139 (2018) - 2017
- [j15]Hyeji Kim, Weihao Gao, Sreeram Kannan, Sewoong Oh, Pramod Viswanath:
Discovering Potential Correlations via Hypercontractivity. Entropy 19(11): 586 (2017) - [j14]Sahand Negahban, Sewoong Oh, Devavrat Shah:
Rank Centrality: Ranking from Pairwise Comparisons. Oper. Res. 65(1): 266-287 (2017) - [j13]Peter Kairouz, Sewoong Oh, Pramod Viswanath:
The Composition Theorem for Differential Privacy. IEEE Trans. Inf. Theory 63(6): 4037-4049 (2017) - [j12]