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ORCIDAlexandros G. Dimakis
Alex Dimakis
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- affiliation: University of Texas at Austin, USA
- affiliation: University of Southern California, Los Angeles, USA
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2020 – today
- 2024
[j45]Adam R. Klivans, Alexandros G. Dimakis, Kristen Grauman, Jonathan I. Tamir, Daniel Jesus Diaz, Karen Davidson
:
Institute for Foundations of Machine Learning (IFML): Advancing AI systems that will transform our world. AI Mag. 45(1): 35-41 (2024)- [j44]Jay Whang, Alliot Nagle, Anish Acharya, Hyeji Kim, Alexandros G. Dimakis:
Neural Distributed Source Coding. IEEE J. Sel. Areas Inf. Theory 5: 493-508 (2024) - [c140]Mi Luo, Zihui Xue, Alex Dimakis, Kristen Grauman:
Put Myself in Your Shoes: Lifting the Egocentric Perspective from Exocentric Videos. ECCV (38) 2024: 407-425 - [c139]Feng Cheng, Mi Luo, Huiyu Wang, Alex Dimakis, Lorenzo Torresani, Gedas Bertasius, Kristen Grauman:
4DIFF: 3D-Aware Diffusion Model for Third-to-First Viewpoint Translation. ECCV (24) 2024: 409-427 - [c138]Yating Wu, Ritika Mangla, Alex Dimakis, Greg Durrett, Junyi Jessy Li:
Which questions should I answer? Salience Prediction of Inquisitive Questions. EMNLP 2024: 19969-19987 - [c137]Giannis Daras, Alex Dimakis, Constantinos Daskalakis:
Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data. ICML 2024 - [i147]Mi Luo, Zihui Xue, Alex Dimakis, Kristen Grauman:
Put Myself in Your Shoes: Lifting the Egocentric Perspective from Exocentric Videos. CoRR abs/2403.06351 (2024) - [i146]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt:
Language models scale reliably with over-training and on downstream tasks. CoRR abs/2403.08540 (2024) - [i145]Asad Aali, Giannis Daras, Brett Levac, Sidharth Kumar, Alexandros G. Dimakis, Jonathan I. Tamir:
Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models trained on Corrupted Data. CoRR abs/2403.08728 (2024) - [i144]Sunny Sanyal, Sujay Sanghavi, Alexandros G. Dimakis:
Pre-training Small Base LMs with Fewer Tokens. CoRR abs/2404.08634 (2024) - [i143]Giannis Daras, Alexandros G. Dimakis, Constantinos Daskalakis:
Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data. CoRR abs/2404.10177 (2024) - [i142]Yating Wu, Ritika Mangla, Alexandros G. Dimakis, Greg Durrett, Junyi Jessy Li:
Which questions should I answer? Salience Prediction of Inquisitive Questions. CoRR abs/2404.10917 (2024) - [i141]Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi:
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors. CoRR abs/2405.19597 (2024) - [i140]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. CoRR abs/2406.11794 (2024) - [i139]Yi-Jen Shih, Zoi Gkalitsiou, Alexandros G. Dimakis, David Harwath:
Self-supervised Speech Models for Word-Level Stuttered Speech Detection. CoRR abs/2409.10704 (2024) - [i138]Giannis Daras, Hyungjin Chung, Chieh-Hsin Lai, Yuki Mitsufuji, Jong Chul Ye, Peyman Milanfar, Alexandros G. Dimakis, Mauricio Delbracio:
A Survey on Diffusion Models for Inverse Problems. CoRR abs/2410.00083 (2024) - [i137]Giannis Daras, Weili Nie, Karsten Kreis, Alex Dimakis, Morteza Mardani, Nikola Borislavov Kovachki, Arash Vahdat:
Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models. CoRR abs/2410.16152 (2024) - 2023
- [j43]Negar Kiyavash, Elias Bareinboim, Todd P. Coleman, Alex Dimakis, Bernhard Schlkopf, Peter Spirtes, Kun Zhang, Robert Nowak:
Editorial Special Issue on Causality: Fundamental Limits and Applications. IEEE J. Sel. Areas Inf. Theory 4: iv (2023) - [j42]Nir Shlezinger, Jay Whang, Yonina C. Eldar, Alexandros G. Dimakis:
Model-Based Deep Learning. Proc. IEEE 111(5): 465-499 (2023) - [j41]Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alex Dimakis, Peyman Milanfar:
Soft Diffusion: Score Matching with General Corruptions. Trans. Mach. Learn. Res. 2023 (2023) - [c136]Sriram Ravula, Varun Gorti, Bo Deng, Swagato Chakraborty, James Pingenot, Bhyrav Mutnury, Douglas Wallace, Douglas Winterberg, Adam R. Klivans, Alexandros G. Dimakis:
One-Dimensional Deep Image Prior for Curve Fitting of S-Parameters from Electromagnetic Solvers. ICCAD 2023: 1-9 - [c135]Tianlong Chen, Chengyue Gong, Daniel Jesus Diaz, Xuxi Chen, Jordan Tyler Wells, Qiang Liu, Zhangyang Wang, Andrew D. Ellington, Alex Dimakis, Adam R. Klivans:
HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing. ICLR 2023 - [c134]Sitan Chen, Giannis Daras, Alex Dimakis:
Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers. ICML 2023: 4462-4484 - [c133]Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis:
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. NeurIPS 2023 - [c132]Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alex Dimakis, Adam R. Klivans:
Ambient Diffusion: Learning Clean Distributions from Corrupted Data. NeurIPS 2023 - [c131]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 J. 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. NeurIPS 2023 - [c130]Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alex Dimakis, Sanjay Shakkottai:
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models. NeurIPS 2023 - [i136]Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis:
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. CoRR abs/2302.09057 (2023) - [i135]Sitan Chen, Giannis Daras, Alexandros G. Dimakis:
Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-Type Samplers. CoRR abs/2303.03384 (2023) - [i134]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) - [i133]Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alexandros G. Dimakis, Adam R. Klivans:
Ambient Diffusion: Learning Clean Distributions from Corrupted Data. CoRR abs/2305.19256 (2023) - [i132]Sriram Ravula, Brett Levac, Ajil Jalal, Jonathan I. Tamir, Alexandros G. Dimakis:
Optimizing Sampling Patterns for Compressed Sensing MRI with Diffusion Generative Models. CoRR abs/2306.03284 (2023) - [i131]Sriram Ravula, Varun Gorti, Bo Deng, Swagato Chakraborty, James Pingenot, Bhyrav Mutnury, Douglas Wallace, Douglas Winterberg, Adam R. Klivans, Alexandros G. Dimakis:
One-Dimensional Deep Image Prior for Curve Fitting of S-Parameters from Electromagnetic Solvers. CoRR abs/2306.04001 (2023) - [i130]Litu Rout, Negin Raoof, Giannis Daras, Constantine Caramanis, Alexandros G. Dimakis, Sanjay Shakkottai:
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models. CoRR abs/2307.00619 (2023) - [i129]Divyanshu Saxena, Nihal Sharma, Donghyun Kim, Rohit Dwivedula, Jiayi Chen, Chenxi Yang, Sriram Ravula, Zichao Hu, Aditya Akella, Sebastian Angel, Joydeep Biswas, Swarat Chaudhuri, Isil Dillig, Alex Dimakis, Philip Brighten Godfrey, Daehyeok Kim, Christopher J. Rossbach, Gang Wang:
On a Foundation Model for Operating Systems. CoRR abs/2312.07813 (2023) - 2022
- [c129]Sriram Ravula, Alexandros G. Dimakis:
One-dimensional Deep Image Prior for Time Series Inverse Problems. IEEECONF 2022: 1005-1009 - [c128]Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G. Dimakis, Peyman Milanfar:
Deblurring via Stochastic Refinement. CVPR 2022: 16272-16282 - [c127]Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis:
Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems. ICML 2022: 4722-4753 - [c126]Giannis Daras, Negin Raoof, Zoi Gkalitsiou, Alex Dimakis:
Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve. NeurIPS 2022 - [c125]Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. NeurIPS 2022 - [i128]Giannis Daras, Alexandros G. Dimakis:
Discovering the Hidden Vocabulary of DALLE-2. CoRR abs/2206.00169 (2022) - [i127]Giannis Daras, Yuval Dagan, Alexandros G. Dimakis, Constantinos Daskalakis:
Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems. CoRR abs/2206.09104 (2022) - [i126]Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alexandros G. Dimakis, Peyman Milanfar:
Soft Diffusion: Score Matching for General Corruptions. CoRR abs/2209.05442 (2022) - [i125]Matt Jordan, Jonathan Hayase, Alexandros G. Dimakis, Sewoong Oh:
Zonotope Domains for Lagrangian Neural Network Verification. CoRR abs/2210.08069 (2022) - [i124]Giannis Daras, Negin Raoof, Zoi Gkalitsiou, Alexandros G. Dimakis:
Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve. CoRR abs/2210.11618 (2022) - [i123]Giannis Daras, Alexandros G. Dimakis:
Multiresolution Textual Inversion. CoRR abs/2211.17115 (2022) - 2021
- [j40]Eren Balevi, Akash S. Doshi, Ajil Jalal, Alexandros G. Dimakis, Jeffrey G. Andrews:
High Dimensional Channel Estimation Using Deep Generative Networks. IEEE J. Sel. Areas Commun. 39(1): 18-30 (2021) - [c124]Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis:
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models. ICML 2021: 2421-2432 - [c123]Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price:
Instance-Optimal Compressed Sensing via Posterior Sampling. ICML 2021: 4709-4720 - [c122]Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price:
Fairness for Image Generation with Uncertain Sensitive Attributes. ICML 2021: 4721-4732 - [c121]Matt Jordan, Alex Dimakis:
Provable Lipschitz Certification for Generative Models. ICML 2021: 5118-5126 - [c120]Jay Whang, Qi Lei, Alex Dimakis:
Solving Inverse Problems with a Flow-based Noise Model. ICML 2021: 11146-11157 - [c119]Jay Whang, Erik M. Lindgren, Alex Dimakis:
Composing Normalizing Flows for Inverse Problems. ICML 2021: 11158-11169 - [c118]Sriram Ravula, Georgios Smyrnis, Matt Jordan, Alexandros G. Dimakis:
Inverse Problems Leveraging Pre-trained Contrastive Representations. NeurIPS 2021: 8753-8765 - [c117]Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir:
Robust Compressed Sensing MRI with Deep Generative Priors. NeurIPS 2021: 14938-14954 - [e1]Alex Smola, Alex Dimakis, Ion Stoica:
Proceedings of the Fourth Conference on Machine Learning and Systems, MLSys 2021, virtual, April 5-9, 2021. mlsys.org 2021 [contents] - [i122]Giannis Daras, Joseph Dean, Ajil Jalal, Alexandros G. Dimakis:
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models. CoRR abs/2102.07364 (2021) - [i121]Jay Whang, Anish Acharya, Hyeji Kim, Alexandros G. Dimakis:
Neural Distributed Source Coding. CoRR abs/2106.02797 (2021) - [i120]Ajil Jalal, Sushrut Karmalkar, Alexandros G. Dimakis, Eric Price:
Instance-Optimal Compressed Sensing via Posterior Sampling. CoRR abs/2106.11438 (2021) - [i119]Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alexandros G. Dimakis, Eric Price:
Fairness for Image Generation with Uncertain Sensitive Attributes. CoRR abs/2106.12182 (2021) - [i118]Matt Jordan, Alexandros G. Dimakis:
Provable Lipschitz Certification for Generative Models. CoRR abs/2107.02732 (2021) - [i117]Ajil Jalal, Marius Arvinte, Giannis Daras, Eric Price, Alexandros G. Dimakis, Jonathan I. Tamir:
Robust Compressed Sensing MRI with Deep Generative Priors. CoRR abs/2108.01368 (2021) - [i116]Sriram Ravula, Georgios Smyrnis, Matt Jordan, Alexandros G. Dimakis:
Inverse Problems Leveraging Pre-trained Contrastive Representations. CoRR abs/2110.07439 (2021) - [i115]Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G. Dimakis, Peyman Milanfar:
Deblurring via Stochastic Refinement. CoRR abs/2112.02475 (2021) - [i114]Giannis Daras, Wen-Sheng Chu, Abhishek Kumar, Dmitry Lagun, Alexandros G. Dimakis:
Solving Inverse Problems with NerfGANs. CoRR abs/2112.09061 (2021) - 2020
- [j39]Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett:
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1(1): 4 (2020) - [j38]Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett:
Deep Learning Techniques for Inverse Problems in Imaging. IEEE J. Sel. Areas Inf. Theory 1(1): 39-56 (2020) - [j37]Netanel Raviv, Itzhak Tamo, Rashish Tandon, Alexandros G. Dimakis:
Gradient Coding From Cyclic MDS Codes and Expander Graphs. IEEE Trans. Inf. Theory 66(12): 7475-7489 (2020) - [c116]Jiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis:
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. AISTATS 2020: 1464-1474 - [c115]Giannis Daras, Augustus Odena, Han Zhang, Alexandros G. Dimakis:
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models. CVPR 2020: 14519-14527 - [c114]Sungsoo Kim, Jin Soo Park, Christos G. Bampis, Jaeseong Lee, Mia K. Markey, Alexandros G. Dimakis, Alan C. Bovik:
Adversarial Video Compression Guided by Soft Edge Detection. ICASSP 2020: 2193-2197 - [c113]Qi Lei, Jason D. Lee, Alex Dimakis, Constantinos Daskalakis:
SGD Learns One-Layer Networks in WGANs. ICML 2020: 5799-5808 - [c112]Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis:
SMYRF - Efficient Attention using Asymmetric Clustering. NeurIPS 2020 - [c111]Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis:
Robust compressed sensing using generative models. NeurIPS 2020 - [c110]Matt Jordan, Alexandros G. Dimakis:
Exactly Computing the Local Lipschitz Constant of ReLU Networks. NeurIPS 2020 - [c109]Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath:
Applications of Common Entropy for Causal Inference. NeurIPS 2020 - [i113]Erik M. Lindgren, Jay Whang, Alexandros G. Dimakis:
Conditional Sampling from Invertible Generative Models with Applications to Inverse Problems. CoRR abs/2002.11743 (2020) - [i112]Matt Jordan, Alexandros G. Dimakis:
Exactly Computing the Local Lipschitz Constant of ReLU Networks. CoRR abs/2003.01219 (2020) - [i111]Jay Whang, Qi Lei, Alexandros G. Dimakis:
Compressed Sensing with Invertible Generative Models and Dependent Noise. CoRR abs/2003.08089 (2020) - [i110]Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett:
Deep Learning Techniques for Inverse Problems in Imaging. CoRR abs/2005.06001 (2020) - [i109]Ajil Jalal, Liu Liu, Alexandros G. Dimakis, Constantine Caramanis:
Robust compressed sensing of generative models. CoRR abs/2006.09461 (2020) - [i108]Giannis Daras, Nikita Kitaev, Augustus Odena, Alexandros G. Dimakis:
SMYRF: Efficient Attention using Asymmetric Clustering. CoRR abs/2010.05315 (2020) - [i107]Nir Shlezinger, Jay Whang, Yonina C. Eldar, Alexandros G. Dimakis:
Model-Based Deep Learning. CoRR abs/2012.08405 (2020)
2010 – 2019
- 2019
- [c108]Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar:
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling. ICML 2019: 6828-6839 - [c107]Qi Lei, Lingfei Wu, Pin-Yu Chen, Alex Dimakis, Inderjit S. Dhillon, Michael Witbrock:
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification. SysML 2019 - [c106]Shanshan Wu, Sujay Sanghavi, Alexandros G. Dimakis:
Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models. NeurIPS 2019: 8069-8079 - [c105]Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi:
Learning Distributions Generated by One-Layer ReLU Networks. NeurIPS 2019: 8105-8115 - [c104]Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis:
Primal-Dual Block Generalized Frank-Wolfe. NeurIPS 2019: 13866-13875 - [c103]Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis:
Inverting Deep Generative models, One layer at a time. NeurIPS 2019: 13910-13919 - [c102]Matt Jordan, Justin Lewis, Alexandros G. Dimakis:
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes. NeurIPS 2019: 14059-14069 - [i106]Matt Jordan, Naren Manoj, Surbhi Goel, Alexandros G. Dimakis:
Quantifying Perceptual Distortion of Adversarial Examples. CoRR abs/1902.08265 (2019) - [i105]Matt Jordan, Justin Lewis, Alexandros G. Dimakis:
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes. CoRR abs/1903.08778 (2019) - [i104]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i103]Sriram Ravula, Alexandros G. Dimakis:
One-dimensional Deep Image Prior for Time Series Inverse Problems. CoRR abs/1904.08594 (2019) - [i102]Qi Lei, Jiacheng Zhuo, Constantine Caramanis, Inderjit S. Dhillon, Alexandros G. Dimakis:
Primal-Dual Block Frank-Wolfe. CoRR abs/1906.02436 (2019) - [i101]Qi Lei, Ajil Jalal, Inderjit S. Dhillon, Alexandros G. Dimakis:
Inverting Deep Generative models, One layer at a time. CoRR abs/1906.07437 (2019) - [i100]Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi:
Learning Distributions Generated by One-Layer ReLU Networks. CoRR abs/1909.01812 (2019) - [i99]Qi Lei, Jason D. Lee, Alexandros G. Dimakis, Constantinos Daskalakis:
SGD Learns One-Layer Networks in WGANs. CoRR abs/1910.07030 (2019) - [i98]Jiacheng Zhuo, Qi Lei, Alexandros G. Dimakis, Constantine Caramanis:
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. CoRR abs/1910.07703 (2019) - [i97]Giannis Daras, Augustus Odena, Han Zhang, Alexandros G. Dimakis:
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models. CoRR abs/1911.12287 (2019) - 2018
- [c101]Ashish Bora, Eric Price, Alexandros G. Dimakis:
AmbientGAN: Generative models from lossy measurements. ICLR 2018 - [c100]Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis, Sriram Vishwanath:
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training. ICLR (Poster) 2018 - [c99]Netanel Raviv, Rashish Tandon, Alex Dimakis, Itzhak Tamo:
Gradient Coding from Cyclic MDS Codes and Expander Graphs. ICML 2018: 4302-4310 - [c98]Erik M. Lindgren, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath:
Experimental Design for Cost-Aware Learning of Causal Graphs. NeurIPS 2018: 5284-5294 - [i96]Yitao Chen, Karthikeyan Shanmugam, Alexandros G. Dimakis:
From Centralized to Decentralized Coded Caching. CoRR abs/1801.07734 (2018) - [i95]David Van Veen, Ajil Jalal, Eric Price, Sriram Vishwanath, Alexandros G. Dimakis:
Compressed Sensing with Deep Image Prior and Learned Regularization. CoRR abs/1806.06438 (2018) - [i94]Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar:
The Sparse Recovery Autoencoder. CoRR abs/1806.10175 (2018) - [i93]Murat Kocaoglu, Sanjay Shakkottai, Alexandros G. Dimakis, Constantine Caramanis, Sriram Vishwanath:
Entropic Latent Variable Discovery. CoRR abs/1807.10399 (2018) - [i92]Erik M. Lindgren, Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath:
Experimental Design for Cost-Aware Learning of Causal Graphs. CoRR abs/1810.11867 (2018) - [i91]Shanshan Wu, Sujay Sanghavi, Alexandros G. Dimakis:
Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models. CoRR abs/1810.11905 (2018) - [i90]Sungsoo Kim, Jin Soo Park, Christos G. Bampis, Jaeseong Lee, Mia K. Markey, Alexandros G. Dimakis, Alan C. Bovik:
Adversarial Video Compression Guided by Soft Edge Detection. CoRR abs/1811.10673 (2018) - [i89]Qi Lei, Lingfei Wu, Pin-Yu Chen, Alexandros G. Dimakis, Inderjit S. Dhillon, Michael Witbrock:
Discrete Attacks and Submodular Optimization with Applications to Text Classification. CoRR abs/1812.00151 (2018) - 2017
- [j36]Anh Le, Arash Saber Tehrani, Alexandros G. Dimakis, Athina Markopoulou:
Recovery of Packet Losses in Wireless Broadcast for Real-Time Applications. IEEE/ACM Trans. Netw. 25(2): 676-689 (2017) - [c97]