Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

ViP: A Differentially Private Foundation Model for Computer Vision.

[BibT_eX]

[DOI]

Yaodong Yu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Differentially Private Representation Learning via Image Captioning.

[BibT_eX]

[DOI]

Tom Sander

Yaodong Yu

Maziar Sanjabi

Alain Oliviero Durmus

Yi Ma

Kamalika Chaudhuri

Chuan Guo

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

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

[BibT_eX]

[DOI]

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

2023

On Tilted Losses in Machine Learning: Theory and Applications.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Samyadeep Basu

Mehrdad Saberi

Shweta Bhardwaj

Atoosa Malemir Chegini

CoRR, 2023

Augmenting CLIP with Improved Visio-Linguistic Reasoning.

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Identifying Interpretable Subspaces in Image Representations.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano.

[BibT_eX]

[DOI]

Chuan Guo

Alexandre Sablayrolles

Maziar Sanjabi

Proceedings of the International Conference on Machine Learning, 2023

Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning.

[BibT_eX]

[DOI]

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

Text2Concept: Concept Activation Vectors Directly from Text.

[BibT_eX]

[DOI]

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

2022

FedShuffle: Recipes for Better Use of Local Work in Federated Learning.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2022

FRAME: Evaluating Simulatability Metrics for Free-Text Rationales.

[BibT_eX]

[DOI]

CoRR, 2022

Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2022

ER-TEST: Evaluating Explanation Regularization Methods for NLP Models.

[BibT_eX]

[DOI]

CoRR, 2022

Understanding Failure Modes of Self-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2022

BARACK: Partially Supervised Group Robustness With Guarantees.

[BibT_eX]

[DOI]

CoRR, 2022

Federated Learning with Partial Model Personalization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

UNIREX: A Unified Learning Framework for Language Model Rationale Extraction.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

ER-Test: Evaluating Explanation Regularization Methods for Language Models.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Detection, Disambiguation, Re-ranking: Autoregressive Entity Linking as a Multi-Task Problem.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision.

[BibT_eX]

[DOI]

CoRR, 2021

Modality-specific Distillation.

[BibT_eX]

[DOI]

CoRR, 2021

Tilted Empirical Risk Minimization.

[BibT_eX]

[DOI]

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

MSD: Saliency-aware Knowledge Distillation for Multimodal Understanding.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Alternating Direction Method of Multipliers for Quantization.

[BibT_eX]

[DOI]

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

2020

Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2020

Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances.

[BibT_eX]

[DOI]

CoRR, 2020

Federated Optimization in Heterogeneous Networks.

[BibT_eX]

[DOI]

Proceedings of the Third Conference on Machine Learning and Systems, 2020

Fair Resource Allocation in Federated Learning.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Building Placements In Urban Modeling Using Conditional Generative Latent Optimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Image Processing, 2020

2019

Multi-theme generative adversarial terrain amplification.

[BibT_eX]

[DOI]

ACM Trans. Graph., 2019

When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima?

[BibT_eX]

[DOI]

CoRR, 2019

Fair Resource Allocation in Federated Learning.

[BibT_eX]

[DOI]

Tian Li

Maziar Sanjabi

Virginia Smith

CoRR, 2019

Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods.

[BibT_eX]

[DOI]

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

Training Generative Networks Using Random Discriminators.

[BibT_eX]

[DOI]

Babak Barazandeh

Meisam Razaviyayn

Maziar Sanjabi

Proceedings of the IEEE Data Science Workshop, 2019

FedDANE: A Federated Newton-Type Method.

[BibT_eX]

[DOI]

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

On the Convergence of Federated Optimization in Heterogeneous Networks.

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[DOI]

CoRR, 2018

Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition.

[BibT_eX]

[DOI]

Maziar Sanjabi

Meisam Razaviyayn

Jason D. Lee

CoRR, 2018

Solving Approximate Wasserstein GANs to Stationarity.

[BibT_eX]

[DOI]

CoRR, 2018

On the Convergence and Robustness of Training GANs with Regularized Optimal Transport.

[BibT_eX]

[DOI]

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

2017

Federated Multi-Task Learning.

[BibT_eX]

[DOI]

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

2016

A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks.

[BibT_eX]

[DOI]

Meisam Razaviyayn

Maziar Sanjabi

Zhi-Quan Luo

Math. Program., 2016

2015

Accelerated Alternating Direction Method of Multipliers.

[BibT_eX]

[DOI]

Mojtaba Kadkhodaie

Konstantina Christakopoulou