Soheil Feizi

According to our database, Soheil Feizi authored at least 143 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

What do we learn from inverting CLIP models?

Hamid Kazemi, Atoosa Malemir Chegini, Jonas Geiping, Soheil Feizi, Tom Goldstein

CoRR, 2024

Fast Adversarial Attacks on Language Models In One GPU Minute.

Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan, Priyatham Kattakinda, Atoosa Malemir Chegini, Soheil Feizi

CoRR, 2024

Data-Centric Debugging: mitigating model failures via targeted image retrieval.

Sahil Singla, Atoosa Malemir Chegini, Mazda Moayeri, Soheil Feizi

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features.

Neha Mukund Kalibhat, Kanika Narang, Hamed Firooz, Maziar Sanjabi, Soheil Feizi

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Strong Baselines for Parameter-Efficient Few-Shot Fine-Tuning.

Samyadeep Basu, Shell Xu Hu, Daniela Massiceti, Soheil Feizi

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses.

Chun Pong Lau, Jiang Liu, Hossein Souri, Wei-An Lin, Soheil Feizi, Rama Chellappa

IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

Identifying and Mitigating the Security Risks of Generative AI.

Clark W. Barrett, Brad Boyd, Elie Bursztein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang

Found. Trends Priv. Secur., 2023

Identifying and Mitigating Model Failures through Few-shot CLIP-aided Diffusion Generation.

Atoosa Malemir Chegini, Soheil Feizi

CoRR, 2023

Instruct2Attack: Language-Guided Semantic Adversarial Attacks.

Jiang Liu, Chen Wei, Yuxiang Guo, Heng Yu, Alan L. Yuille, Soheil Feizi, Chun Pong Lau, Rama Chellappa

CoRR, 2023

Online Advertisements with LLMs: Opportunities and Challenges.

Soheil Feizi, MohammadTaghi Hajiaghayi, Keivan Rezaei, Suho Shin

CoRR, 2023

Localizing and Editing Knowledge in Text-to-Image Generative Models.

Samyadeep Basu, Nanxuan Zhao, Vlad I. Morariu, Soheil Feizi, Varun Manjunatha

CoRR, 2023

EditVal: Benchmarking Diffusion Based Text-Guided Image Editing Methods.

Samyadeep Basu, Mehrdad Saberi, Shweta Bhardwaj, Atoosa Malemir Chegini, Daniela Massiceti, Maziar Sanjabi, Shell Xu Hu, Soheil Feizi

CoRR, 2023

PRIME: Prioritizing Interpretability in Failure Mode Extraction.

Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri, Soheil Feizi

CoRR, 2023

Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks.

Mehrdad Saberi, Vinu Sankar Sadasivan, Keivan Rezaei, Aounon Kumar, Atoosa Malemir Chegini, Wenxiao Wang, Soheil Feizi

CoRR, 2023

Certifying LLM Safety against Adversarial Prompting.

Aounon Kumar, Chirag Agarwal, Suraj Srinivas, Soheil Feizi, Hima Lakkaraju

CoRR, 2023

Identifying and Mitigating the Security Risks of Generative AI.

Clark W. Barrett, Brad Boyd, Ellie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang

CoRR, 2023

Augmenting CLIP with Improved Visio-Linguistic Reasoning.

Samyadeep Basu, Maziar Sanjabi, Daniela Massiceti, Shell Xu Hu, Soheil Feizi

CoRR, 2023

On Practical Aspects of Aggregation Defenses against Data Poisoning Attacks.

Wenxiao Wang, Soheil Feizi

CoRR, 2023

Provable Robustness for Streaming Models with a Sliding Window.

Aounon Kumar, Vinu Sankar Sadasivan, Soheil Feizi

CoRR, 2023

Adversarial Robustness of Learning-based Static Malware Classifiers.

Shoumik Saha, Wenxiao Wang, Yigitcan Kaya, Soheil Feizi

CoRR, 2023

Can AI-Generated Text be Reliably Detected?

Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, Wenxiao Wang, Soheil Feizi

CoRR, 2023

Diffused Redundancy in Pre-trained Representations.

Vedant Nanda, Till Speicher, John P. Dickerson, Krishna P. Gummadi, Soheil Feizi, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases.

Mazda Moayeri, Wenxiao Wang, Sahil Singla, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Exploring Geometry of Blind Spots in Vision models.

Sriram Balasubramanian, Gaurang Sriramanan, Vinu Sankar Sadasivan, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Temporal Robustness against Data poisoning.

Wenxiao Wang, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Run-off Election: Improved Provable Defense against Data Poisoning Attacks.

Keivan Rezaei, Kiarash Banihashem, Atoosa Malemir Chegini, Soheil Feizi

Proceedings of the International Conference on Machine Learning, 2023

Text-To-Concept (and Back) via Cross-Model Alignment.

Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi

Proceedings of the International Conference on Machine Learning, 2023

Identifying Interpretable Subspaces in Image Representations.

Neha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi

Proceedings of the International Conference on Machine Learning, 2023

Certifiably Robust Policy Learning against Adversarial Multi-Agent Communication.

Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Provable Robustness against Wasserstein Distribution Shifts via Input Randomization.

Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Hard-Meta-Dataset++: Towards Understanding Few-Shot Performance on Difficult Tasks.

Samyadeep Basu, Megan Stanley, John Bronskill, Soheil Feizi, Daniela Massiceti

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Improved Input Masking for Convolutional Neural Networks.

Sriram Balasubramanian, Soheil Feizi

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

CUDA: Convolution-Based Unlearnable Datasets.

Vinu Sankar Sadasivan, Mahdi Soltanolkotabi, Soheil Feizi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Text2Concept: Concept Activation Vectors Directly from Text.

Mazda Moayeri, Keivan Rezaei, Maziar Sanjabi, Soheil Feizi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Adapting Self-Supervised Representations to Multi-Domain Setups.

Neha Mukund Kalibhat, Samuel Sharpe, Jeremy Goodsitt, C. Bayan Bruss, Soheil Feizi

Proceedings of the 34th British Machine Vision Conference 2023, 2023

Goal-Conditioned Q-learning as Knowledge Distillation.

Alexander Levine, Soheil Feizi

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Mutual Adversarial Training: Learning Together is Better Than Going Alone.

Jiang Liu, Chun Pong Lau, Hossein Souri, Soheil Feizi, Rama Chellappa

IEEE Trans. Inf. Forensics Secur., 2022

Spuriosity Rankings: Sorting Data for Spurious Correlation Robustness.

Mazda Moayeri, Wenxiao Wang, Sahil Singla, Soheil Feizi

CoRR, 2022

Towards Better Input Masking for Convolutional Neural Networks.

Sriram Balasubramanian, Soheil Feizi

CoRR, 2022

Invariant Learning via Diffusion Dreamed Distribution Shifts.

Priyatham Kattakinda, Alexander Levine, Soheil Feizi

CoRR, 2022

Data-Centric Debugging: mitigating model failures via targeted data collection.

Sahil Singla, Atoosa Malemir Chegini, Mazda Moayeri, Soheil Feizi

CoRR, 2022

Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems.

Yanchao Sun, Ruijie Zheng, Parisa Hassanzadeh, Yongyuan Liang, Soheil Feizi, Sumitra Ganesh, Furong Huang

CoRR, 2022

Interpretable Mixture of Experts for Structured Data.

Aya Abdelsalam Ismail, Sercan Ö. Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister

CoRR, 2022

Core Risk Minimization using Salient ImageNet.

Sahil Singla, Mazda Moayeri, Soheil Feizi

CoRR, 2022

Understanding Failure Modes of Self-Supervised Learning.

Neha Mukund Kalibhat, Kanika Narang, Liang Tan, Hamed Firooz, Maziar Sanjabi, Soheil Feizi

CoRR, 2022

Certifying Model Accuracy under Distribution Shifts.

Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi

CoRR, 2022

Toward Efficient Robust Training against Union of $\ell_p$ Threat Models.

Gaurang Sriramanan, Maharshi Gor, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Explicit Tradeoffs between Adversarial and Natural Distributional Robustness.

Mazda Moayeri, Kiarash Banihashem, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Hard ImageNet: Segmentations for Objects with Strong Spurious Cues.

Mazda Moayeri, Sahil Singla, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improved techniques for deterministic l2 robustness.

Sahil Singla, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Lethal Dose Conjecture on Data Poisoning.

Wenxiao Wang, Alexander Levine, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FOCUS: Familiar Objects in Common and Uncommon Settings.

Priyatham Kattakinda, Soheil Feizi

Proceedings of the International Conference on Machine Learning, 2022

Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation.

Wenxiao Wang, Alexander Levine, Soheil Feizi

Proceedings of the International Conference on Machine Learning, 2022

Policy Smoothing for Provably Robust Reinforcement Learning.

Aounon Kumar, Alexander Levine, Soheil Feizi

Proceedings of the Tenth International Conference on Learning Representations, 2022

Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100.

Sahil Singla, Surbhi Singla, Soheil Feizi

Proceedings of the Tenth International Conference on Learning Representations, 2022

Salient ImageNet: How to discover spurious features in Deep Learning?

Sahil Singla, Soheil Feizi

Proceedings of the Tenth International Conference on Learning Representations, 2022

A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes.

Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection.

Jiang Liu, Alexander Levine, Chun Pong Lau, Rama Chellappa, Soheil Feizi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Provable Adversarial Robustness for Fractional Lp Threat Models.

Alexander Levine, Soheil Feizi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

On Hard Episodes in Meta-Learning.

Samyadeep Basu, Amr Sharaf, Nicolò Fusi, Soheil Feizi

CoRR, 2021

Causal ImageNet: How to discover spurious features in Deep Learning?

Sahil Singla, Soheil Feizi

CoRR, 2021

Householder Activations for Provable Robustness against Adversarial Attacks.

Sahil Singla, Surbhi Singla, Soheil Feizi

CoRR, 2021

Understanding Overparameterization in Generative Adversarial Networks.

Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi

CoRR, 2021

Improved, Deterministic Smoothing for L1 Certified Robustness.

Alexander Levine, Soheil Feizi

CoRR, 2021

Unsupervised anomaly detection with adversarial mirrored autoencoders.

Gowthami Somepalli, Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Improving Deep Learning Interpretability by Saliency Guided Training.

Aya Abdelsalam Ismail, Héctor Corrada Bravo, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Skew Orthogonal Convolutions.

Sahil Singla, Soheil Feizi

Proceedings of the 38th International Conference on Machine Learning, 2021

Improved, Deterministic Smoothing for L₁ Certified Robustness.

Alexander Levine, Soheil Feizi

Proceedings of the 38th International Conference on Machine Learning, 2021

Perceptual Adversarial Robustness: Defense Against Unseen Threat Models.

Cassidy Laidlaw, Sahil Singla, Soheil Feizi

Proceedings of the 9th International Conference on Learning Representations, 2021

Influence Functions in Deep Learning Are Fragile.

Samyadeep Basu, Phillip Pope, Soheil Feizi

Proceedings of the 9th International Conference on Learning Representations, 2021

Understanding Over-parameterization in Generative Adversarial Networks.

Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi

Proceedings of the 9th International Conference on Learning Representations, 2021

Fantastic Four: Differentiable and Efficient Bounds on Singular Values of Convolution Layers.

Sahil Singla, Soheil Feizi

Proceedings of the 9th International Conference on Learning Representations, 2021

Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks.

Alexander Levine, Soheil Feizi

Proceedings of the 9th International Conference on Learning Representations, 2021

Low Curvature Activations Reduce Overfitting in Adversarial Training.

Vasu Singla, Sahil Singla, Soheil Feizi, David Jacobs

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Sample Efficient Detection and Classification of Adversarial Attacks via Self-Supervised Embeddings.

Mazda Moayeri, Soheil Feizi

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Fairness Through Robustness: Investigating Robustness Disparity in Deep Learning.

Vedant Nanda, Samuel Dooley, Sahil Singla, Soheil Feizi, John P. Dickerson

Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

GANs with Conditional Independence Graphs: On Subadditivity of Probability Divergences.

Mucong Ding, Constantinos Daskalakis, Soheil Feizi

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Winning Lottery Tickets in Deep Generative Models.

Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Spectral Alignment of Graphs.

Soheil Feizi, Gerald T. Quon, Mariana Recamonde Mendoza, Muriel Médard, Manolis Kellis, Ali Jadbabaie

IEEE Trans. Netw. Sci. Eng., 2020

Understanding GANs in the LQG Setting: Formulation, Generalization and Stability.

Soheil Feizi, Farzan Farnia, Tony Ginart, David Tse

IEEE J. Sel. Areas Inf. Theory, 2020

Tight Second-Order Certificates for Randomized Smoothing.

Alexander Levine, Aounon Kumar, Thomas A. Goldstein, Soheil Feizi

CoRR, 2020

GANs with Variational Entropy Regularizers: Applications in Mitigating the Mode-Collapse Issue.

Pirazh Khorramshahi, Hossein Souri, Rama Chellappa, Soheil Feizi

CoRR, 2020

Deep Partition Aggregation: Provable Defense against General Poisoning Attacks.

Alexander Levine, Soheil Feizi

CoRR, 2020

Mirrored Autoencoders with Simplex Interpolation for Unsupervised Anomaly Detection.

Yexin Wu, Yogesh Balaji, Bhanukiran Vinzamuri, Soheil Feizi

CoRR, 2020

Subadditivity of Probability Divergences on Bayes-Nets with Applications to Time Series GANs.

Mucong Ding, Constantinos Daskalakis, Soheil Feizi

CoRR, 2020

Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks.

Wei-An Lin, Chun Pong Lau, Alexander Levine, Rama Chellappa, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Certifying Confidence via Randomized Smoothing.

Aounon Kumar, Alexander Levine, Soheil Feizi, Tom Goldstein

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Benchmarking Deep Learning Interpretability in Time Series Predictions.

Aya Abdelsalam Ismail, Mohamed K. Gunady, Héctor Corrada Bravo, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust Optimal Transport with Applications in Generative Modeling and Domain Adaptation.

Yogesh Balaji, Rama Chellappa, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

(De)Randomized Smoothing for Certifiable Defense against Patch Attacks.

Alexander Levine, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness.

Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi

Proceedings of the 37th International Conference on Machine Learning, 2020

On Second-Order Group Influence Functions for Black-Box Predictions.

Samyadeep Basu, Xuchen You, Soheil Feizi

Proceedings of the 37th International Conference on Machine Learning, 2020

Second-Order Provable Defenses against Adversarial Attacks.

Sahil Singla, Soheil Feizi

Proceedings of the 37th International Conference on Machine Learning, 2020

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

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

Adversarial Robustness of Flow-Based Generative Models.

Phillip Pope, Yogesh Balaji, Soheil Feizi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks.

Alexander Levine, Soheil Feizi

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Maximum Likelihood Embedding of Logistic Random Dot Product Graphs.

Luke J. O'Connor, Muriel Médard, Soheil Feizi

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation.

Alexander Levine, Soheil Feizi

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Adversarially Robust Distillation.

Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Network Infusion to Infer Information Sources in Networks.

Soheil Feizi, Muriel Médard, Gerald T. Quon, Manolis Kellis, Ken Duffy

IEEE Trans. Netw. Sci. Eng., 2019

Playing it Safe: Adversarial Robustness with an Abstain Option.

Cassidy Laidlaw, Soheil Feizi

CoRR, 2019

Bounding Singular Values of Convolution Layers.

Sahil Singla, Soheil Feizi

CoRR, 2019

Strong Baseline Defenses Against Clean-Label Poisoning Attacks.

Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson

CoRR, 2019

Interpretable Adversarial Training for Text.

Samuel Barham, Soheil Feizi

CoRR, 2019

Certifiably Robust Interpretation in Deep Learning.

Alexander Levine, Sahil Singla, Soheil Feizi

CoRR, 2019

Robustness Certificates Against Adversarial Examples for ReLU Networks.

Sahil Singla, Soheil Feizi

CoRR, 2019

Normalized Wasserstein Distance for Mixture Distributions with Applications in Adversarial Learning and Domain Adaptation.

Yogesh Balaji, Rama Chellappa, Soheil Feizi

CoRR, 2019

Compressing GANs using Knowledge Distillation.

Angeline Aguinaldo, Ping-Yeh Chiang, Alexander Gain, Ameya Patil, Kolten Pearson, Soheil Feizi

CoRR, 2019

Functional Adversarial Attacks.

Cassidy Laidlaw, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Input-Cell Attention Reduces Vanishing Saliency of Recurrent Neural Networks.

Aya Abdelsalam Ismail, Mohamed K. Gunady, Luiz Pessoa, Héctor Corrada Bravo, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Quantum Wasserstein Generative Adversarial Networks.

Shouvanik Chakrabarti, Yiming Huang, Tongyang Li, Soheil Feizi, Xiaodi Wu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation.

Sahil Singla, Eric Wallace, Shi Feng, Soheil Feizi

Proceedings of the 36th International Conference on Machine Learning, 2019

Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs.

Yogesh Balaji, Hamed Hassani, Rama Chellappa, Soheil Feizi

Proceedings of the 36th International Conference on Machine Learning, 2019

Are adversarial examples inevitable?

Ali Shafahi, W. Ronny Huang, Christoph Studer, Soheil Feizi, Tom Goldstein

Proceedings of the 7th International Conference on Learning Representations, 2019

Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation.

Yogesh Balaji, Rama Chellappa, Soheil Feizi

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Porcupine Neural Networks: Approximating Neural Network Landscapes.

Soheil Feizi, Hamid Javadi, Jesse M. Zhang, David Tse

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Network Maximal Correlation.

Soheil Feizi, Ali Makhdoumi, Ken Duffy, Manolis Kellis, Muriel Médard

IEEE Trans. Netw. Sci. Eng., 2017

Understanding GANs: the LQG Setting.

Soheil Feizi, Changho Suh, Fei Xia, David Tse

CoRR, 2017

Porcupine Neural Networks: (Almost) All Local Optima are Global.

Soheil Feizi, Hamid Javadi, Jesse M. Zhang, David Tse

CoRR, 2017

Maximally Correlated Principal Component Analysis.

Soheil Feizi, David Tse

CoRR, 2017

Tensor Biclustering.

Soheil Feizi, Hamid Javadi, David Tse

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

A memristor based binary multiplier.

Saeed Haghiri, Ali Nemati, Soheil Feizi, Amirali Amirsoleimani, Arash Ahmadi, Majid Ahmadi

Proceedings of the 30th IEEE Canadian Conference on Electrical and Computer Engineering, 2017

2016

On the analysis of complex networks: fundamental limits, scalable algorithms, and applications.

Soheil Feizi-Khankandi

PhD thesis, 2016

Spectral Alignment of Networks.

Soheil Feizi, Gerald T. Quon, Mariana Recamonde Mendoza, Muriel Médard, Manolis Kellis, Ali Jadbabaie

CoRR, 2016

2015

Integrative analysis of 111 reference human epigenomes Open.

Roadmap 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 T. 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, Kyle 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

Nat., 2015

A Perspective on Future Research Directions in Information Theory.

Jeffrey G. Andrews, Alexandros G. Dimakis, Lara Dolecek, Michelle Effros, Muriel Médard, Olgica Milenkovic, Andrea Montanari, Sriram Vishwanath, Edmund M. Yeh, Randall Berry, Ken R. Duffy, Soheil Feizi, Saul Kato, Manolis Kellis, Stuart Licht, Jon Sorenson, Lav R. Varshney, Haris Vikalo

CoRR, 2015

2014

Backward Adaptation for Power Efficient Sampling.

Soheil Feizi, Georgios Angelopoulos, Vivek K. Goyal, Muriel Médard

IEEE Trans. Signal Process., 2014

On Network Functional Compression.

Soheil Feizi, Muriel Médard

IEEE Trans. Inf. Theory, 2014

Biclustering Usinig Message Passing.

Luke J. O'Connor, Soheil Feizi

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Tunable sparse network coding for multicast networks.

Soheil Feizi, Daniel E. Lucani, Chres W. Sørensen, Ali Makhdoumi, Muriel Médard

Proceedings of the International Symposium on Network Coding, 2014

2012

Time-Stampless Adaptive Nonuniform Sampling for Stochastic Signals.

Soheil Feizi, Vivek K. Goyal, Muriel Médard

IEEE Trans. Signal Process., 2012

Empirical rate-distortion study of compressive sensing-based joint source-channel coding.

Muriel L. Rambeloarison, Soheil Feizi, Georgios Angelopoulos, Muriel Médard

Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012

2011

A power efficient sensing/communication scheme: Joint source-channel-network coding by using compressive sensing.

Soheil Feizi, Muriel Médard

Proceedings of the 49th Annual Allerton Conference on Communication, 2011

2010

Cases where finding the minimum entropy coloring of a characteristic graph is a polynomial time problem.

Soheil Feizi, Muriel Médard

Proceedings of the IEEE International Symposium on Information Theory, 2010

Compressive sensing over networks.

Soheil Feizi, Muriel Médard, Michelle Effros

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

Locally Adaptive Sampling.

Soheil Feizi, Vivek K. Goyal, Muriel Médard

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009

Robust Audio Data Hiding Using Correlated Quantization With Histogram-Based Detector.

Mohammad Ali Akhaee, Mohammad Javad Saberian, Soheil Feizi, Farokh Marvasti

IEEE Trans. Multim., 2009

Impulsive Noise Cancellation Based on Soft Decision and Recursion.

Sina Zahedpour, Soheil Feizi, Arash Amini, Mahmoud Ferdosizadeh Naeiny, Farrokh Marvasti

IEEE Trans. Instrum. Meas., 2009

Multi-Functional Compression with Side Information.

Soheil Feizi-Khankandi, Muriel Médard

Proceedings of the Global Communications Conference, 2009. GLOBECOM 2009, Honolulu, Hawaii, USA, 30 November, 2009

When do only sources need to compute? On functional compression in tree networks.

Soheil Feizi, Muriel Médard

Proceedings of the 47th Annual Allerton Conference on Communication, 2009

2008

Lower and Upper Bounds for Throughput Capacity of a Cognitive Ad Hoc Network Overlaid on a Cellular Network.

Soheil Feizi-Khankandi, Farid Ashtiani

Proceedings of the WCNC 2008, IEEE Wireless Communications & Networking Conference, March 31 2008, 2008

Impulsive noise cancellation using CFAR and iterative techniques.

Sina Zahedpour, Soheil Feizi, Arash Amini, Mahmoud Ferdosizadeh Naeiny, Farokh Marvasti

Proceedings of the 2008 International Conference on Telecommunications, 2008

Salt and pepper noise removal for image signals.

Soheil Feizi, Sina Zahedpour, Mahdi Soltanolkotabi, Arash Amini, Farokh Marvasti

Proceedings of the 2008 International Conference on Telecommunications, 2008