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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
- 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) - [c131]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 - [c130]Sitan Chen, Giannis Daras, Alex Dimakis:
Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers. ICML 2023: 4462-4484 - [i135]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) - [i134]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) - [i133]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) - [i132]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) - [i131]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) - [i130]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) - [i129]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) - 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 Machine Learning and Systems 2021, 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. MLSys 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 R. 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]Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi:
Entropic Causal Inference. AAAI 2017: 1156-1162 - [c96]Karthikeyan Shanmugam, Alexandros G. Dimakis, Jaime Llorca, Antonia Maria Tulino:
A unified Ruzsa-Szemerédi framework for finite-length coded caching. ACSSC 2017: 631-635 - [c95]Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai:
Contextual Bandits with Latent Confounders: An NMF Approach. AISTATS 2017: 518-527 - [c94]Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Sahand N. Negahban, Joydeep Ghosh:
Scalable Greedy Feature Selection via Weak Submodularity. AISTATS 2017: 1560-1568 - [c93]Ashish Bora, Ajil Jalal, Eric Price, Alexandros G. Dimakis:
Compressed Sensing using Generative Models. ICML 2017: 537-546 - [c92]Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Joydeep Ghosh, Sahand N. Negahban:
On Approximation Guarantees for Greedy Low Rank Optimization. ICML 2017: 1837-1846 - [c91]Murat Kocaoglu, Alex Dimakis, Sriram Vishwanath:
Cost-Optimal Learning of Causal Graphs. ICML 2017: 1875-1884 - [c90]Erik M. Lindgren, Alexandros G. Dimakis, Adam R. Klivans:
Exact MAP Inference by Avoiding Fractional Vertices. ICML 2017: 2120-2129 - [c89]Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Identifying Best Interventions through Online Importance Sampling. ICML 2017: 3057-3066 - [c88]Rashish Tandon, Qi Lei, Alexandros G. Dimakis, Nikos Karampatziakis:
Gradient Coding: Avoiding Stragglers in Distributed Learning. ICML 2017: 3368-3376 - [c87]Karthikeyan Shanmugam, Antonia Maria Tulino, Alexandros G. Dimakis:
Coded caching with linear subpacketization is possible using Ruzsa-Szeméredi graphs. ISIT 2017: 1237-1241 - [c86]Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi:
Entropie causality anc greedy minimum entropy coupling. ISIT 2017: 1465-1469 - [c85]Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Model-Powered Conditional Independence Test. NIPS 2017: 2951-2961 - [c84]Ethan R. Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi:
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. NIPS 2017: 4044-4054 - [i88]Rajat Sen, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Causal Best Intervention Identification via Importance Sampling. CoRR abs/1701.02789 (2017) - [i87]Karthikeyan Shanmugam, Antonia Maria Tulino, Alexandros G. Dimakis:
Coded Caching with Linear Subpacketization is Possible using Ruzsa-Szeméredi Graphs. CoRR abs/1701.07115 (2017) - [i86]Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath, Babak Hassibi:
Entropic Causality and Greedy Minimum Entropy Coupling. CoRR abs/1701.08254 (2017) - [i85]Murat Kocaoglu, Alexandros G. Dimakis, Sriram Vishwanath:
Cost-Optimal Learning of Causal Graphs. CoRR abs/1703.02645 (2017) - [i84]Ethan R. Elenberg, Alexandros G. Dimakis, Moran Feldman, Amin Karbasi:
Streaming Weak Submodularity: Interpreting Neural Networks on the Fly. CoRR abs/1703.02647 (2017) - [i83]Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sujay Sanghavi:
Sparse Quadratic Logistic Regression in Sub-quadratic Time. CoRR abs/1703.02682 (2017) - [i82]Erik M. Lindgren, Alexandros G. Dimakis, Adam R. Klivans:
Exact MAP Inference by Avoiding Fractional Vertices. CoRR abs/1703.02689 (2017) - [i81]Erik M. Lindgren, Shanshan Wu, Alexandros G. Dimakis:
Leveraging Sparsity for Efficient Submodular Data Summarization. CoRR abs/1703.02690 (2017) - [i80]Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Sahand N. Negahban:
On Approximation Guarantees for Greedy Low Rank Optimization. CoRR abs/1703.02721 (2017) - [i79]Rajiv Khanna, Ethan R. Elenberg, Alexandros G. Dimakis, Sahand N. Negahban, Joydeep Ghosh:
Scalable Greedy Feature Selection via Weak Submodularity. CoRR abs/1703.02723 (2017) - [i78]Ashish Bora, Ajil Jalal, Eric Price, Alexandros G. Dimakis:
Compressed Sensing using Generative Models. CoRR abs/1703.03208 (2017) - [i77]Netanel Raviv, Itzhak Tamo, Rashish Tandon, Alexandros G. Dimakis:
Gradient Coding from Cyclic MDS Codes and Expander Graphs. CoRR abs/1707.03858 (2017) - [i76]Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis, Sriram Vishwanath:
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training. CoRR abs/1709.02023 (2017) - [i75]Rajat Sen, Ananda Theertha Suresh, Karthikeyan Shanmugam, Alexandros G. Dimakis, Sanjay Shakkottai:
Model-Powered Conditional Independence Test. CoRR abs/1709.06138 (2017) - [i74]Andrew Ilyas, Ajil Jalal, Eirini Asteri, Constantinos Daskalakis, Alexandros G. Dimakis:
The Robust Manifold Defense: Adversarial Training using Generative Models. CoRR abs/1712.09196 (2017) - 2016
- [j35]Ankit Singh Rawat, Zhao Song, Alexandros G. Dimakis, Anna Gál:
Batch Codes Through Dense Graphs Without Short Cycles. IEEE Trans. Inf. Theory 62(4): 1592-1604 (2016) - [j34]Ankit Singh Rawat, Dimitris S. Papailiopoulos, Alexandros G. Dimakis, Sriram Vishwanath:
Locality and Availability in Distributed Storage. IEEE Trans. Inf. Theory 62(8): 4481-4493 (2016) - [j33]Karthikeyan Shanmugam, Mingyue Ji, Antonia Maria Tulino, Jaime Llorca, Alexandros G. Dimakis:
Finite-Length Analysis of Caching-Aided Coded Multicasting. IEEE Trans. Inf. Theory 62(10): 5524-5537 (2016) - [j32]Itzhak Tamo, Dimitris S. Papailiopoulos, Alexandros G. Dimakis:
Optimal Locally Repairable Codes and Connections to Matroid Theory. IEEE Trans. Inf. Theory 62(12): 6661-6671 (2016) - [j31]