Alex Dimakis

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 28

Top Topics

Image Generation

Sensitive Attributes

Inverse Problems

Generative Model

Top Venues

IEEE J. Sel. Areas Inf. Theory

Publications

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 (2024)
Mi Luo, Zihui Xue, Alex Dimakis, Kristen Grauman
Put Myself in Your Shoes: Lifting the Egocentric Perspective from Exocentric Videos. CoRR (2024)
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 (2023)
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)
Giannis Daras, Kulin Shah, Yuval Dagan, Aravind Gollakota, Alex Dimakis, Adam R. Klivans
Ambient Diffusion: Learning Clean Distributions from Corrupted Data. NeurIPS (2023)
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 (2023)
Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent. NeurIPS (2023)
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)
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 (2023)
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)
Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alex Dimakis, Peyman Milanfar
Soft Diffusion: Score Matching with General Corruptions. Trans. Mach. Learn. Res. 2023 (2023)
Sitan Chen, Giannis Daras, Alex Dimakis
Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers. ICML (2023)
Matt Jordan, Jonathan Hayase, Alex Dimakis, Sewoong Oh
Zonotope Domains for Lagrangian Neural Network Verification. NeurIPS (2022)
Giannis Daras, Negin Raoof, Zoi Gkalitsiou, Alex Dimakis
Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve. NeurIPS (2022)
Giannis Daras, Yuval Dagan, Alex Dimakis, Constantinos Daskalakis
Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems. ICML (2022)
Jay Whang, Erik M. Lindgren, Alex Dimakis
Composing Normalizing Flows for Inverse Problems. ICML (2021)
Ajil Jalal, Sushrut Karmalkar, Jessica Hoffmann, Alex Dimakis, Eric Price
Fairness for Image Generation with Uncertain Sensitive Attributes. ICML (2021)
Ajil Jalal, Sushrut Karmalkar, Alex Dimakis, Eric Price
Instance-Optimal Compressed Sensing via Posterior Sampling. ICML (2021)
Jay Whang, Qi Lei, Alex Dimakis
Solving Inverse Problems with a Flow-based Noise Model. ICML (2021)
Giannis Daras, Joseph Dean, Ajil Jalal, Alex Dimakis
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models. ICML (2021)
Matt Jordan, Alex Dimakis
Provable Lipschitz Certification for Generative Models. ICML (2021)
Jiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls. AISTATS (2020)
Qi Lei, Jason D. Lee, Alex Dimakis, Constantinos Daskalakis
SGD Learns One-Layer Networks in WGANs. ICML (2020)
Richard G. Baraniuk, Alex Dimakis, Negar Kiyavash, Sewoong Oh, Rebecca Willett
Guest Editorial. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Qi Lei, Lingfei Wu, Pin-Yu Chen, Alex Dimakis, Inderjit S. Dhillon, Michael J. Witbrock
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification. MLSys (2019)
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)
Netanel Raviv, Rashish Tandon, Alex Dimakis, Itzhak Tamo
Gradient Coding from Cyclic MDS Codes and Expander Graphs. ICML (2018)
Murat Kocaoglu, Alex Dimakis, Sriram Vishwanath
Cost-Optimal Learning of Causal Graphs. ICML (2017)
Alex Dimakis
Session TP4b: Distributed storage systems. ACSCC (2011)