Tom Goldstein
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
117
Venues
19
Active years
2004–2025
Best venue rank
A*
Where they publish
Papers
117 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AAAI | Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data? | Michael-Andrei Panaitescu-Liess, Zora Che, Bang An, Yuancheng Xu, Pankayaraj Pathmanathan, Souradip Chakraborty, Sicheng Zhu, Tom Goldstein, Furong Huang |
| 2025 | CVPR | Speedy-Splat: Fast 3D Gaussian Splatting with Sparse Pixels and Sparse Primitives. | Alex Hanson, Allen Tu, Geng Lin, Vasu Singla, Matthias Zwicker, Tom Goldstein |
| 2025 | CVPR | PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting. | Alex Hanson, Allen Tu, Vasu Singla, Mayuka Jayawardhana, Matthias Zwicker, Tom Goldstein |
| 2025 | CVPR | Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models. | Reza Shirkavand, Peiran Yu, Shangqian Gao, Gowthami Somepalli, Tom Goldstein, Heng Huang |
| 2025 | ICCV | ARGUS: Hallucination and Omission Evaluation in Video-LLMs. | Ruchit Rawal, Reza Shirkavand, Heng Huang, Gowthami Somepalli, Tom Goldstein |
| 2025 | ICCV | Zero-Shot Vision Encoder Grafting via LLM Surrogates. | Kaiyu Yue, Vasu Singla, Menglin Jia, John Kirchenbauer, Rifaa Qadri, Zikui Cai, Abhinav Bhatele, Furong Huang, Tom Goldstein |
| 2025 | ICLR | LiveBench: A Challenging, Contamination-Limited LLM Benchmark. | Colin White, Samuel Dooley, Manley Roberts, Arka Pal, Benjamin Feuer, Siddhartha Jain, Ravid Shwartz-Ziv, Neel Jain, Khalid Saifullah, Sreemanti Dey, Shubh-Agrawal, Sandeep Singh Sandha, Siddartha V. Naidu, Chinmay Hegde, Yann LeCun, Tom Goldstein, Willie Neiswanger, Micah Goldblum |
| 2025 | NAACL | LLM-Generated Passphrases That Are Secure and Easy to Remember. | Jie S. Li, Jonas Geiping, Micah Goldblum, Aniruddha Saha, Tom Goldstein |
| 2025 | NAACL | Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. | Xiyao Wang, Jiuhai Chen, Zhaoyang Wang, Yuhang Zhou, Yiyang Zhou, Huaxiu Yao, Tianyi Zhou, Tom Goldstein, Parminder Bhatia, Taha A. Kass-Hout, Furong Huang, Cao Xiao |
| 2024 | CVPR | Object Recognition as Next Token Prediction. | Kaiyu Yue, Bor-Chun Chen, Jonas Geiping, Hengduo Li, Tom Goldstein, Ser-Nam Lim |
| 2024 | ECCV | Investigating Style Similarity in Diffusion Models. | Gowthami Somepalli, Anubhav Gupta, Kamal Gupta, Shramay Palta, Micah Goldblum, Jonas Geiping, Abhinav Shrivastava, Tom Goldstein |
| 2024 | ICASSP | FedAQT: Accurate Quantized Training with Federated Learning. | Renkun Ni, Yonghui Xiao, Phoenix Meadowlark, Oleg Rybakov, Tom Goldstein, Ananda Theertha Suresh, Ignacio Lpez-Moreno, Mingqing Chen, Rajiv Mathews |
| 2024 | ICLR | Universal Guidance for Diffusion Models. | Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein |
| 2024 | ICLR | NEFTune: Noisy Embeddings Improve Instruction Finetuning. | Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein |
| 2024 | ICLR | On the Reliability of Watermarks for Large Language Models. | John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein |
| 2024 | ICML | WAVES: Benchmarking the Robustness of Image Watermarks. | Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang |
| 2024 | ICML | ODIN: Disentangled Reward Mitigates Hacking in RLHF. | Lichang Chen, Chen Zhu, Jiuhai Chen, Davit Soselia, Tianyi Zhou, Tom Goldstein, Heng Huang, Mohammad Shoeybi, Bryan Catanzaro |
| 2024 | ICML | InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models. | Lichang Chen, Jiuhai Chen, Tom Goldstein, Heng Huang, Tianyi Zhou |
| 2024 | ICML | Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text. | Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein |
| 2024 | ICRA | Hierarchical Point Attention for Indoor 3D Object Detection. | Manli Shu, Le Xue, Ning Yu, Roberto Martn-Martn, Caiming Xiong, Tom Goldstein, Juan Carlos Niebles, Ran Xu |
| 2024 | SC | Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers. | Siddharth Singh, Prajwal Singhania, Aditya K. Ranjan, John Kirchenbauer, Jonas Geiping, Yuxin Wen, Neel Jain, Abhimanyu Hans, Manli Shu, Aditya Tomar, Tom Goldstein, Abhinav Bhatele |
| 2023 | AIES | A Deep Dive into Dataset Imbalance and Bias in Face Identification. | Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein |
| 2023 | BMVC | Unifying the Harmonic Analysis of Adversarial Attacks and Robustness. | Shishira R. Maiya, Max Ehrlich, Vatsal Agarwal, Ser-Nam Lim, Tom Goldstein, Abhinav Shrivastava |
| 2023 | CVPR | Universal Guidance for Diffusion Models. | Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein |
| 2023 | CVPR | Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. | Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein |
| 2023 | ICASSP | STYX: Adaptive Poisoning Attacks Against Byzantine-Robust Defenses in Federated Learning. | Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein |
| 2023 | ICLR | Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent. | Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein |
| 2023 | ICLR | Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation. | Hong-Min Chu, Jonas Geiping, Liam H. Fowl, Micah Goldblum, Tom Goldstein |
| 2023 | ICLR | Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models. | Liam H. Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein |
| 2023 | ICLR | How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization. | Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson |
| 2023 | ICLR | Provable Robustness against Wasserstein Distribution Shifts via Input Randomization. | Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi |
| 2023 | ICLR | Transfer Learning with Deep Tabular Models. | Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum |
| 2023 | ICLR | Seeing in Words: Learning to Classify through Language Bottlenecks. | Khalid Saifullah, Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein |
| 2023 | ICLR | Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. | Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein |
| 2023 | ICLR | Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness. | Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang |
| 2023 | ICML | Cramming: Training a Language Model on a single GPU in one day. | Jonas Geiping, Tom Goldstein |
| 2023 | ICML | A Watermark for Large Language Models. | John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein |
| 2023 | ICML | GOAT: A Global Transformer on Large-scale Graphs. | Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein |
| 2022 | AAAI | Towards Transferable Adversarial Attacks on Vision Transformers. | Zhipeng Wei, Jingjing Chen, Micah Goldblum, Zuxuan Wu, Tom Goldstein, Yu-Gang Jiang |
| 2022 | AISTATS | Learning Revenue-Maximizing Auctions With Differentiable Matching. | Michael J. Curry, Uro Lyi, Tom Goldstein, John P. Dickerson |
| 2022 | CVPR | Robust Optimization as Data Augmentation for Large-scale Graphs. | Kezhi Kong, Guohao Li, Mucong Ding, Zuxuan Wu, Chen Zhu, Bernard Ghanem, Gavin Taylor, Tom Goldstein |
| 2022 | CVPR | Poisons that are learned faster are more effective. | Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein |
| 2022 | CVPR | Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. | Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein |
| 2022 | ICLR | Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. | Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf |
| 2022 | ICLR | Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models. | Liam H. Fowl, Jonas Geiping, Wojciech Czaja, Micah Goldblum, Tom Goldstein |
| 2022 | ICLR | Stochastic Training is Not Necessary for Generalization. | Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein |
| 2022 | ICLR | The Close Relationship Between Contrastive Learning and Meta-Learning. | Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein |
| 2022 | ICLR | The Uncanny Similarity of Recurrence and Depth. | Avi Schwarzschild, Arjun Gupta, Amin Ghiasi, Micah Goldblum, Tom Goldstein |
| 2022 | ICLR | Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions. | Chen Zhu, Zheng Xu, Mingqing Chen, Jakub Konecn, Andrew Hard, Tom Goldstein |
| 2022 | ICML | Certified Neural Network Watermarks with Randomized Smoothing. | Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein |
| 2022 | ICML | Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations. | Amin Ghiasi, Hamid Kazemi, Steven Reich, Chen Zhu, Micah Goldblum, Tom Goldstein |
| 2022 | ICML | Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification. | Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein |
| 2021 | AAAI | Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks. | Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang |
| 2021 | ACSSC | Hybrid Jammer Mitigation for All-Digital mmWave Massive MU-MIMO. | Gian Marti, Oscar Castaeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer |
| 2021 | ICASSP | Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. | Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta |
| 2021 | ICLR | LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition. | Valeriia Cherepanova, Micah Goldblum, Harrison Foley, Shiyuan Duan, John P. Dickerson, Gavin Taylor, Tom Goldstein |
| 2021 | ICLR | Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. | Jonas Geiping, Liam H. Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein |
| 2021 | ICLR | WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic. | Renkun Ni, Hong-Min Chu, Oscar Castaeda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein |
| 2021 | ICLR | The Intrinsic Dimension of Images and Its Impact on Learning. | Phillip Pope, Chen Zhu, Ahmed Abdelkader, Micah Goldblum, Tom Goldstein |
| 2021 | ICML | Data Augmentation for Meta-Learning. | Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein |
| 2021 | ICML | Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks. | Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P. Dickerson, Tom Goldstein |
| 2021 | ICRA | Adversarial Differentiable Data Augmentation for Autonomous Systems. | Manli Shu, Yu Shen, Ming C. Lin, Tom Goldstein |
| 2020 | AAAI | Adversarially Robust Distillation. | Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein |
| 2020 | AAAI | Universal Adversarial Training. | Ali Shafahi, Mahyar Najibi, Zheng Xu, John P. Dickerson, Larry S. Davis, Tom Goldstein |
| 2020 | ACSSC | Hardware-Friendly Two-Stage Spatial Equalization for All-Digital mmWave Massive MU-MIMO. | Oscar Castaeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer |
| 2020 | BMVC | Making L-BFGS Work with Industrial-Strength Nets. | Abhay Kumar Yadav, Tom Goldstein, David W. Jacobs |
| 2020 | CISS | MSE-Optimal Neural Network Initialization via Layer Fusion. | Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer |
| 2020 | ECCV | Deep k-NN Defense Against Clean-Label Data Poisoning Attacks. | Neehar Peri, Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson |
| 2020 | ECCV | Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors. | Zuxuan Wu, Ser-Nam Lim, Larry S. Davis, Tom Goldstein |
| 2020 | ICASSP | Headless Horseman: Adversarial Attacks on Transfer Learning Models. | Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu |
| 2020 | ICASSP | Soft-Output Finite Alphabet Equalization for mmWave Massive MIMO. | Oscar Castaeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer |
| 2020 | ICASSP | Witchcraft: Efficient PGD Attacks with Random Step Size. | Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi |
| 2020 | ICLR | Certified Defenses for Adversarial Patches. | Ping-yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein |
| 2020 | ICLR | Breaking Certified Defenses: Semantic Adversarial Examples with Spoofed robustness Certificates. | Amin Ghiasi, Ali Shafahi, Tom Goldstein |
| 2020 | ICLR | Truth or backpropaganda? An empirical investigation of deep learning theory. | Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein |
| 2020 | ICLR | Adversarially robust transfer learning. | Ali Shafahi, Parsa Saadatpanah, Chen Zhu, Amin Ghiasi, Christoph Studer, David W. Jacobs, Tom Goldstein |
| 2020 | ICLR | Network Deconvolution. | Chengxi Ye, Matthew Evanusa, Hua He, Anton Mitrokhin, Tom Goldstein, James A. Yorke, Cornelia Fermller, Yiannis Aloimonos |
| 2020 | ICLR | FreeLB: Enhanced Adversarial Training for Natural Language Understanding. | Chen Zhu, Yu Cheng, Zhe Gan, Siqi Sun, Tom Goldstein, Jingjing Liu |
| 2020 | ICML | Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks. | Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein |
| 2020 | ICML | Certified Data Removal from Machine Learning Models. | Chuan Guo, Tom Goldstein, Awni Y. Hannun, Laurens van der Maaten |
| 2020 | ICML | Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness. | Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi |
| 2020 | ICML | Adversarial Attacks on Copyright Detection Systems. | Parsa Saadatpanah, Ali Shafahi, Tom Goldstein |
| 2020 | ICML | The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent. | Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein |
| 2019 | ACSSC | Finite-Alphabet Wiener Filter Precoding for mmWave Massive MU-MIMO Systems. | Oscar Castaeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer |
| 2019 | BMVC | Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing. | Ali Shafahi, Amin Ghiasi, Mahyar Najibi, Furong Huang, John P. Dickerson, Tom Goldstein |
| 2019 | ICCV | ACE: Adapting to Changing Environments for Semantic Segmentation. | Zuxuan Wu, Xin Wang, Joseph Gonzalez, Tom Goldstein, Larry Davis |
| 2019 | ICLR | Are adversarial examples inevitable? | Ali Shafahi, W. Ronny Huang, Christoph Studer, Soheil Feizi, Tom Goldstein |
| 2019 | ICML | Transferable Clean-Label Poisoning Attacks on Deep Neural Nets. | Chen Zhu, W. Ronny Huang, Hengduo Li, Gavin Taylor, Christoph Studer, Tom Goldstein |
| 2018 | CISS | PhaseLin: Linear phase retrieval. | Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer |
| 2018 | ECCV | DCAN: Dual Channel-Wise Alignment Networks for Unsupervised Scene Adaptation. | Zuxuan Wu, Xintong Han, Yen-Liang Lin, Mustafa Gkhan Uzunbas, Tom Goldstein, Ser-Nam Lim, Larry S. Davis |
| 2018 | GLOBECOM | Unsupervised Charting of Wireless Channels. | Said Medjkouh, Emre Gnltas, Tom Goldstein, Olav Tirkkonen, Christoph Studer |
| 2018 | ICLR | Stabilizing Adversarial Nets with Prediction Methods. | Abhay Kumar Yadav, Sohil Shah, Zheng Xu, David W. Jacobs, Tom Goldstein |
| 2018 | ICML | Linear Spectral Estimators and an Application to Phase Retrieval. | Ramina Ghods, Andrew S. Lan, Tom Goldstein, Christoph Studer |
| 2018 | ISCAS | VLSI Design of a 3-bit Constant-Modulus Precoder for Massive MU-MIMO. | Oscar Castaeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer |
| 2017 | AAAI | Scalable Classifiers with ADMM and Transpose Reduction. | Gavin Taylor, Zheng Xu, Tom Goldstein |
| 2017 | ACSSC | PhasePack: A phase retrieval library. | Rohan Chandra, Ziyuan Zhong, Justin Hontz, Val McCulloch, Christoph Studer, Tom Goldstein |
| 2017 | AISTATS | Adaptive ADMM with Spectral Penalty Parameter Selection. | Zheng Xu, Mrio A. T. Figueiredo, Tom Goldstein |
| 2017 | AISTATS | Automated Inference with Adaptive Batches. | Soham De, Abhay Kumar Yadav, David W. Jacobs, Tom Goldstein |
| 2017 | CVPR | Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation. | Zheng Xu, Mrio A. T. Figueiredo, Xiaoming Yuan, Christoph Studer, Tom Goldstein |
| 2017 | CVPR | A New Rank Constraint on Multi-view Fundamental Matrices, and Its Application to Camera Location Recovery. | Soumyadip Sengupta, Tal Amir, Meirav Galun, Tom Goldstein, David W. Jacobs, Amit Singer, Ronen Basri |
| 2017 | ICASSP | POKEMON: A non-linear beamforming algorithm for 1-bit massive MIMO. | Oscar Castaeda, Tom Goldstein, Christoph Studer |
| 2017 | ICASSP | Son of Zorn's lemma: Targeted style transfer using instance-aware semantic segmentation. | Carlos Domingo Castillo, Soham De, Xintong Han, Bharat Singh, Abhay Kumar Yadav, Tom Goldstein |
| 2017 | ICML | Adaptive Consensus ADMM for Distributed Optimization. | Zheng Xu, Gavin Taylor, Hao Li, Mrio A. T. Figueiredo, Xiaoming Yuan, Tom Goldstein |
| 2017 | ICML | Convex Phase Retrieval without Lifting via PhaseMax. | Tom Goldstein, Christoph Studer |
| 2017 | ISCAS | FPGA design of low-complexity joint channel estimation and data detection for large SIMO wireless systems. | Oscar Castaeda, Tom Goldstein, Christoph Studer |
| 2016 | ACSSC | Nonlinear 1-bit precoding for massive MU-MIMO with higher-order modulation. | Sven Jacobsson, Giuseppe Durisi, Mikael Coldrey, Tom Goldstein, Christoph Studer |
| 2016 | ACSSC | Decentralized data detection for massive MU-MIMO on a Xeon Phi cluster. | Kaipeng Li, Yujun Chen, Rishi Sharan, Tom Goldstein, Joseph R. Cavallaro, Christoph Studer |
| 2016 | AISTATS | Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction. | Tom Goldstein, Gavin Taylor, Kawika Barabin, Kent Sayre |
| 2016 | CVPR | Estimating Sparse Signals with Smooth Support via Convex Programming and Block Sparsity. | Sohil Shah, Tom Goldstein, Christoph Studer |
| 2016 | ECCV | Biconvex Relaxation for Semidefinite Programming in Computer Vision. | Sohil Shah, Abhay Kumar Yadav, Carlos Domingo Castillo, David W. Jacobs, Christoph Studer, Tom Goldstein |
| 2016 | ICDM | Efficient Distributed SGD with Variance Reduction. | Soham De, Tom Goldstein |
| 2016 | ICML | Dealbreaker: A Nonlinear Latent Variable Model for Educational Data. | Andrew S. Lan, Tom Goldstein, Richard G. Baraniuk, Christoph Studer |
| 2016 | ICML | Training Neural Networks Without Gradients: A Scalable ADMM Approach. | Gavin Taylor, Ryan Burmeister, Zheng Xu, Bharat Singh, Ankit B. Patel, Tom Goldstein |
| 2016 | ISCAS | FPGA design of approximate semidefinite relaxation for data detection in large MIMO wireless systems. | Oscar Castaeda, Tom Goldstein, Christoph Studer |
| 2016 | SDM | Deterministic Column Sampling for Low-Rank Matrix Approximation: Nystrm vs. Incomplete Cholesky Decomposition. | Raajen Patel, Tom Goldstein, Eva L. Dyer, Azalia Mirhoseini, Richard G. Baraniuk |
| 2013 | ICASSP | Adaptive step size selection for optimization via the ski rental problem. | Amirali Aghazadeh, Ali Ayremlou, Daniel D. Calderon, Tom Goldstein, Raajen Patel, Divyanshu Vats, Richard G. Baraniuk |
| 2004 | ICASSP | Perceptual speech quality assessment in acoustic and binaural applications. | Tom Goldstein, Antony W. Rix |