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2024

Strong Baselines for Parameter-Efficient Few-Shot Fine-TuningSamyadeep Basu, Shell Xu Hu, Daniela Massiceti, Soheil Feizi. AAAI 2024: 11024-11031 [doi]

Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative FeaturesNeha Mukund Kalibhat, Kanika Narang, Hamed Firooz, Maziar Sanjabi, Soheil Feizi. AAAI 2024: 13031-13039 [doi]

2023

Goal-Conditioned Q-learning as Knowledge DistillationAlexander Levine 0001, Soheil Feizi. AAAI 2023: 8500-8509 [doi]

Interpolated Joint Space Adversarial Training for Robust and Generalizable DefensesChun Pong Lau 0001, Jiang Liu 0014, Hossein Souri, Wei-An Lin, Soheil Feizi, Rama Chellappa. pami, 45(11):13054-13067, November 2023. [doi]

Temporal Robustness against Data poisoningWenxiao Wang 0002, Soheil Feizi. nips 2023: [doi]

Exploring Geometry of Blind Spots in Vision modelsSriram Balasubramanian, Gaurang Sriramanan, Vinu Sankar Sadasivan, Soheil Feizi. nips 2023: [doi]

Towards Improved Input Masking for Convolutional Neural NetworksSriram Balasubramanian, Soheil Feizi. iccv 2023: 1855-1865 [doi]

Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult TasksSamyadeep Basu, Megan Stanley, John Bronskill, Soheil Feizi, Daniela Massiceti. iclr 2023: [doi]

Identifying Interpretable Subspaces in Image RepresentationsNeha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi. icml 2023: 15623-15638 [doi]

Adapting Self-Supervised Representations to Multi-Domain SetupsNeha Mukund Kalibhat, Samuel Sharpe, Jeremy Goodsitt, C. Bayan Bruss, Soheil Feizi. bmvc 2023: 353-355 [doi]

Provable Robustness against Wasserstein Distribution Shifts via Input RandomizationAounon Kumar, Alexander Levine 0001, Tom Goldstein, Soheil Feizi. iclr 2023: [doi]

Text2Concept: Concept Activation Vectors Directly from TextMazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi. cvpr 2023: 3744-3749 [doi]

Spuriosity Rankings: Sorting Data to Measure and Mitigate BiasesMazda Moayeri, Wenxiao Wang 0002, Sahil Singla 0002, Soheil Feizi. nips 2023: [doi]

Text-To-Concept (and Back) via Cross-Model AlignmentMazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi. icml 2023: 25037-25060 [doi]

Diffused Redundancy in Pre-trained RepresentationsVedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller. nips 2023: [doi]

Run-off Election: Improved Provable Defense against Data Poisoning AttacksKeivan Rezaei, Kiarash Banihashem, Atoosa Malemir Chegini, Soheil Feizi. icml 2023: 29030-29050 [doi]

CUDA: Convolution-Based Unlearnable DatasetsVinu Sankar Sadasivan, Mahdi Soltanolkotabi, Soheil Feizi. cvpr 2023: 3862-3871 [doi]

Certifiably Robust Policy Learning against Adversarial Multi-Agent CommunicationYanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang. iclr 2023: [doi]

2022

Provable Adversarial Robustness for Fractional Lp Threat ModelsAlexander Levine 0001, Soheil Feizi. aistats 2022: 9908-9942 [doi]

Improved techniques for deterministic l2 robustnessSahil Singla 0002, Soheil Feizi. nips 2022: [doi]

Improved Certified Defenses against Data Poisoning with (Deterministic) Finite AggregationWenxiao Wang 0002, Alexander Levine 0001, Soheil Feizi. icml 2022: 22769-22783 [doi]

Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100Sahil Singla 0002, Surbhi Singla, Soheil Feizi. iclr 2022: [doi]

Salient ImageNet: How to discover spurious features in Deep Learning?Sahil Singla 0002, Soheil Feizi. iclr 2022: [doi]

Lethal Dose Conjecture on Data PoisoningWenxiao Wang 0002, Alexander Levine 0001, Soheil Feizi. nips 2022: [doi]

FOCUS: Familiar Objects in Common and Uncommon SettingsPriyatham Kattakinda, Soheil Feizi. icml 2022: 10825-10847 [doi]

Policy Smoothing for Provably Robust Reinforcement LearningAounon Kumar, Alexander Levine 0001, Soheil Feizi. iclr 2022: [doi]

Mutual Adversarial Training: Learning Together is Better Than Going AloneJiang Liu, Chun Pong Lau 0001, Hossein Souri, Soheil Feizi, Rama Chellappa. tifs, 17:2364-2377, 2022. [doi]

Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch DetectionJiang Liu, Alexander Levine 0001, Chun Pong Lau 0001, Rama Chellappa, Soheil Feizi. cvpr 2022: 14953-14962 [doi]

A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual AttributesMazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi. cvpr 2022: 19065-19075 [doi]

Hard ImageNet: Segmentations for Objects with Strong Spurious CuesMazda Moayeri, Sahil Singla 0002, Soheil Feizi. nips 2022: [doi]

Explicit Tradeoffs between Adversarial and Natural Distributional RobustnessMazda Moayeri, Kiarash Banihashem, Soheil Feizi. nips 2022: [doi]

Toward Efficient Robust Training against Union of $\ell_p$ Threat ModelsGaurang Sriramanan, Maharshi Gor, Soheil Feizi. nips 2022: [doi]

2021

1 Certified RobustnessAlexander Levine 0001, Soheil Feizi. icml 2021: 6254-6264 [doi]

Deep Partition Aggregation: Provable Defenses against General Poisoning AttacksAlexander Levine 0001, Soheil Feizi. iclr 2021: [doi]

Skew Orthogonal ConvolutionsSahil Singla 0002, Soheil Feizi. icml 2021: 9756-9766 [doi]

Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution LayersSahil Singla 0002, Soheil Feizi. iclr 2021: [doi]

Understanding Over-parameterization in Generative Adversarial NetworksYogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi. iclr 2021: [doi]

Influence Functions in Deep Learning Are FragileSamyadeep Basu, Phillip Pope, Soheil Feizi. iclr 2021: [doi]

GANs with Conditional Independence Graphs: On Subadditivity of Probability DivergencesMucong Ding, Constantinos Daskalakis, Soheil Feizi. aistats 2021: 3709-3717 [doi]

Improving Deep Learning Interpretability by Saliency Guided TrainingAya Abdelsalam Ismail, Héctor Corrada Bravo, Soheil Feizi. nips 2021: 26726-26739 [doi]

Winning Lottery Tickets in Deep Generative ModelsNeha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi. AAAI 2021: 8038-8046 [doi]

Perceptual Adversarial Robustness: Defense Against Unseen Threat ModelsCassidy Laidlaw, Sahil Singla 0002, Soheil Feizi. iclr 2021: [doi]

Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised EmbeddingsMazda Moayeri, Soheil Feizi. iccv 2021: 7657-7666 [doi]

Fairness Through Robustness: Investigating Robustness Disparity in Deep LearningVedant Nanda, Samuel Dooley, Sahil Singla 0002, Soheil Feizi, John P. Dickerson. fat 2021: 466-477 [doi]

Low Curvature Activations Reduce Overfitting in Adversarial TrainingVasu Singla, Sahil Singla 0002, Soheil Feizi, David Jacobs. iccv 2021: 16403-16413 [doi]

Unsupervised anomaly detection with adversarial mirrored autoencodersGowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi. uai 2021: 365-375 [doi]

2020

Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial AttacksAlexander Levine 0001, Soheil Feizi. aistats 2020: 3938-3947 [doi]

(De)Randomized Smoothing for Certifiable Defense against Patch AttacksAlexander Levine 0001, Soheil Feizi. nips 2020: [doi]

Second-Order Provable Defenses against Adversarial AttacksSahil Singla 0002, Soheil Feizi. icml 2020: 8981-8991 [doi]

Robust Optimal Transport with Applications in Generative Modeling and Domain AdaptationYogesh Balaji, Rama Chellappa, Soheil Feizi. nips 2020: [doi]

On Second-Order Group Influence Functions for Black-Box PredictionsSamyadeep Basu, Xuchen You, Soheil Feizi. icml 2020: 715-724 [doi]

Understanding GANs in the LQG Setting: Formulation, Generalization and StabilitySoheil Feizi, Farzan Farnia, Tony Ginart, David Tse. jsait, 1(1):304-311, 2020. [doi]

Spectral Alignment of GraphsSoheil Feizi, Gerald T. Quon, Mariana Recamonde Mendoza, Muriel Médard, Manolis Kellis, Ali Jadbabaie. tnse, 7(3):1182-1197, 2020. [doi]

Adversarially Robust DistillationMicah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein. AAAI 2020: 3996-4003 [doi]

Benchmarking Deep Learning Interpretability in Time Series PredictionsAya Abdelsalam Ismail, Mohamed K. Gunady, Héctor Corrada Bravo, Soheil Feizi. nips 2020: [doi]

Curse of Dimensionality on Randomized Smoothing for Certifiable RobustnessAounon Kumar, Alexander Levine 0001, Tom Goldstein, Soheil Feizi. icml 2020: 5458-5467 [doi]

Certifying Confidence via Randomized SmoothingAounon Kumar, Alexander Levine 0001, Soheil Feizi, Tom Goldstein. nips 2020: [doi]

Robustness Certificates for Sparse Adversarial Attacks by Randomized AblationAlexander Levine, Soheil Feizi. AAAI 2020: 4585-4593 [doi]

Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial AttacksWei-An Lin, Chun Pong Lau 0001, Alexander Levine 0001, Rama Chellappa, Soheil Feizi. nips 2020: [doi]

Maximum Likelihood Embedding of Logistic Random Dot Product GraphsLuke J. O'Connor, Muriel Médard, Soheil Feizi. AAAI 2020: 5289-5297 [doi]

Deep k-NN Defense Against Clean-Label Data Poisoning AttacksNeehar Peri, Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson. eccv 2020: 55-70 [doi]

Adversarial Robustness of Flow-Based Generative ModelsPhillip Pope, Yogesh Balaji, Soheil Feizi. aistats 2020: 3795-3805 [doi]

2019

Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain AdaptationYogesh Balaji, Rama Chellappa, Soheil Feizi. iccv 2019: 6499-6507 [doi]

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANsYogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi. icml 2019: 414-423 [doi]

Quantum Wasserstein Generative Adversarial NetworksShouvanik Chakrabarti, Yiming Huang, Tongyang Li, Soheil Feizi, Xiaodi Wu. nips 2019: 6778-6789 [doi]

Network Infusion to Infer Information Sources in NetworksSoheil Feizi, Muriel Médard, Gerald T. Quon, Manolis Kellis, Ken Duffy. tnse, 6(3):402-417, 2019. [doi]

Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural NetworksAya Abdelsalam Ismail, Mohamed K. Gunady, Luiz Pessoa, Héctor Corrada Bravo, Soheil Feizi. nips 2019: 10813-10823 [doi]

Functional Adversarial AttacksCassidy Laidlaw, Soheil Feizi. nips 2019: 10408-10418 [doi]

Are adversarial examples inevitable?Ali Shafahi, W. Ronny Huang, Christoph Studer, Soheil Feizi, Tom Goldstein. iclr 2019: [doi]

Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning InterpretationSahil Singla, Eric Wallace, Shi Feng, Soheil Feizi. icml 2019: 5848-5856 [doi]

2018

Porcupine Neural Networks: Approximating Neural Network LandscapesSoheil Feizi, Hamid Javadi, Jesse Zhang, David Tse. nips 2018: 4836-4846 [doi]

2017

2015

Integrative analysis of 111 reference human epigenomes OpenRoadmap Epigenomics Consortium, Anshul Kundaje, Wouter Meuleman, Jason Ernst, Misha Bilenky, Angela Yen, Alireza Heravi Moussavi, Pouya Kheradpour, ZhiZhuo Zhang, Jianrong Wang, Michael J. Ziller, Viren Amin, John W. Whitaker, Matthew D. Schultz, Lucas D. Ward, Abhishek Sarkar, Gerald Quon, Richard S. Sandstrom, Matthew L. Eaton, Yi-Chieh Wu, Andreas R. Pfenning, Xinchen Wang, Melina Claussnitzer, Yaping Liu, Cristian Coarfa, R. Alan Harris, Noam Shoresh, Charles B. Epstein, Elizabeta Gjoneska, Danny Leung, Wei Xie, R. David Hawkins, Ryan Lister, Chibo Hong, Philippe Gascard, Andrew J. Mungall, Richard A. Moore, Eric Chuah, Angela Tam, Theresa K. Canfield, R. Scott Hansen, Rajinder Kaul, Peter J. Sabo, Mukul S. Bansal, Annaick Carles, Jesse R. Dixon, Kai-How Farh, Soheil Feizi, Rosa Karlic, Ah-Ram Kim, Ashwinikumar Kulkarni, Daofeng Li, Rebecca F. Lowdon, GiNell Elliott, Tim R. Mercer, Shane J. Neph, Vitor Onuchic, Paz Polak, Nisha Rajagopal, Pradipta Ray, Richard C. Sallari, Kyle T. Siebenthall, Nicholas A. Sinnott-Armstrong, Michael Stevens, Robert E. Thurman, Jie Wu, Bo Zhang, Xin Zhou, Arthur E. Beaudet, Laurie A. Boyer, Philip L. De Jager, Peggy J. Farnham, Susan J. Fisher, David Haussler, Steven J. M. Jones, Wei Li, Marco A. Marra, Michael T. McManus, Shamil R. Sunyaev, James A. Thomson, Thea D. Tlsty, Li-Huei Tsai, Wei Wang, Robert A. Waterland, Michael Q. Zhang, Lisa H. Chadwick, Bradley E. Bernstein, Joseph F. Costello, Joseph R. Ecker, Martin Hirst, Alexander Meissner, Aleksandar Milosavljevic, Bing Ren, John A. Stamatoyannopoulos, Ting Wang, Manolis Kellis. nature, 518(7539):317-330, 2015. [doi]

2014

2012

Time-stampless adaptive nonuniform sampling for stochastic signalsSoheil Feizi, Vivek K. Goyal, Muriel Médard. icassp 2012: 3809-3812 [doi]

Time-Stampless Adaptive Nonuniform Sampling for Stochastic SignalsSoheil Feizi, Vivek K. Goyal, Muriel Médard. tsp, 60(10):5440-5450, 2012. [doi]

Empirical rate-distortion study of compressive sensing-based joint source-channel codingMuriel L. Rambeloarison, Soheil Feizi, Georgios Angelopoulos, Muriel Médard. acssc 2012: 1224-1228 [doi]

2011

A power efficient sensing/communication scheme: Joint source-channel-network coding by using compressive sensingSoheil Feizi, Muriel Médard. allerton 2011: 1048-1054 [doi]

2010

Compressive sensing over networksSoheil Feizi, Muriel Médard, Michelle Effros. allerton 2010: 1129-1136 [doi]

Cases where finding the minimum entropy coloring of a characteristic graph is a polynomial time problemSoheil Feizi, Muriel Médard. isit 2010: 116-120 [doi]

Locally Adaptive SamplingSoheil Feizi, Vivek K. Goyal, Muriel Médard. allerton 2010: 152-159 [doi]

2009

2008

Salt and pepper noise removal for image signalsSoheil Feizi, Sina Zahedpour, Mahdi Soltanolkotabi, Arash Amini, Farokh Marvasti. ICT 2008: 1-5 [doi]

Impulsive noise cancellation using CFAR and iterative techniquesSina Zahedpour, Soheil Feizi, Arash Amini, Mahmoud Ferdosizadeh Naeiny, Farokh Marvasti. ICT 2008: 1-5 [doi]

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