Baharan Mirzasoleiman

According to our database, Baharan Mirzasoleiman authored at least 67 papers between 2009 and 2024.

Collaborative distances:

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

2024

Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks.

Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman

CoRR, 2024

Memory-efficient Training of LLMs with Larger Mini-batches.

Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman

CoRR, 2024

Make the Most of Your Data: Changing the Training Data Distribution to Improve In-distribution Generalization Performance.

Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman

CoRR, 2024

SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models.

Yu Yang, Siddhartha Mishra, Jeffrey N. Chiang, Baharan Mirzasoleiman

CoRR, 2024

A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction.

Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman, Omid Abari

CoRR, 2024

Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks.

Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman

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

Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings.

Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman

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

NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction.

Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman, Omid Abari

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

Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift.

Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Investigating the Benefits of Projection Head for Representation Learning.

Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality.

Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity.

Siddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias.

Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

On the Fairness of Time-Critical Influence Maximization in Social Networks.

Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla

IEEE Trans. Knowl. Data Eng., March, 2023

Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent.

Lauren Watson, Eric Gan, Mohan Dantam, Baharan Mirzasoleiman, Rik Sarkar

CoRR, 2023

Ordering for Non-Replacement SGD.

Yuetong Xu, Baharan Mirzasoleiman

CoRR, 2023

Towards Mitigating Spurious Correlations in the Wild: A Benchmark & a more Realistic Dataset.

Siddharth Joshi, Yu Yang, Yihao Xue, Wenhan Yang, Baharan Mirzasoleiman

CoRR, 2023

Eliminating Spurious Correlations from Pre-trained Models via Data Mixing.

Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman

CoRR, 2023

Robust Contrastive Language-Image Pretraining against Adversarial Attacks.

Wenhan Yang, Baharan Mirzasoleiman

CoRR, 2023

Contrastive Learning under Heterophily.

Wenhan Yang, Baharan Mirzasoleiman

CoRR, 2023

Data-Efficient Contrastive Self-supervised Learning: Easy Examples Contribute the Most.

Siddharth Joshi, Baharan Mirzasoleiman

CoRR, 2023

Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization.

Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp, Baharan Mirzasoleiman

CoRR, 2023

Robust Contrastive Language-Image Pretraining against Data Poisoning and Backdoor Attacks.

Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman

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

Robust Learning with Progressive Data Expansion Against Spurious Correlation.

Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu

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

Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression.

Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023

Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least.

Siddharth Joshi, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023

Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning.

Yu Yang, Besmira Nushi, Hamid Palangi, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023

Towards Sustainable Learning: Coresets for Data-efficient Deep Learning.

Yu Yang, Hao Kang, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2023

A Self-supervised Framework for Improved Data-Driven Monitoring of Stress via Multi-Modal Passive Sensing.

Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh

Proceedings of the IEEE International Conference on Digital Health, 2023

NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training.

Neha Prakriya, Yu Yang, Baharan Mirzasoleiman, Cho-Jui Hsieh, Jason Cong

Proceedings of the 15th ACM/USENIX Workshop on Hot Topics in Storage and File Systems, 2023

High Probability Bounds for Stochastic Continuous Submodular Maximization.

Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks.

Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman

CoRR, 2022

Superior generalization of smaller models in the presence of significant label noise.

Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman

CoRR, 2022

Analytical Models for Motifs in Temporal Networks.

Alexandra M. Porter, Baharan Mirzasoleiman, Jure Leskovec

Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack.

Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman

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

Data-Efficient Augmentation for Training Neural Networks.

Tian Yu Liu, Baharan Mirzasoleiman

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

Not All Poisons are Created Equal: Robust Training against Data Poisoning.

Yu Yang, Tian Yu Liu, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2022

Investigating Why Contrastive Learning Benefits Robustness against Label Noise.

Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2022

Adaptive Second Order Coresets for Data-efficient Machine Learning.

Omead Pooladzandi, David Davini, Baharan Mirzasoleiman

Proceedings of the International Conference on Machine Learning, 2022

On the Fairness of Time-Critical Influence Maximization in Social Networks (Extended Abstract).

Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Passive Monitoring of Physiological Precursors of Stress Leveraging Smartwatch Data.

Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

CrossWalk: Fairness-Enhanced Node Representation Learning.

Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Analytical Models for Motifs in Temporal Networks: Discovering Trends and Anomalies.

Alexandra M. Porter, Baharan Mirzasoleiman, Jure Leskovec

CoRR, 2021

GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning.

KrishnaTeja Killamsetty, Durga Sivasubramanian, Baharan Mirzasoleiman, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer

CoRR, 2021

2020

Coresets for Robust Training of Neural Networks against Noisy Labels.

Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec

CoRR, 2020

Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples.

Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Coresets for Robust Training of Deep Neural Networks against Noisy Labels.

Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec

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

Coresets for Data-efficient Training of Machine Learning Models.

Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec

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

Selection via Proxy: Efficient Data Selection for Deep Learning.

Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia

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

2019

Data Sketching for Faster Training of Machine Learning Models.

Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec

CoRR, 2019

Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization.

Saeed Vahidian, Alexander Cloninger, Baharan Mirzasoleiman

CoRR, 2019

2018

Dynamic Network Model from Partial Observations.

Elahe Ghalebi, Baharan Mirzasoleiman, Radu Grosu, Jure Leskovec

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

Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly.

Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Big Data Summarization Using Submodular Functions.

Baharan Mirzasoleiman

PhD thesis, 2017

Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten".

Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause

Proceedings of the 34th International Conference on Machine Learning, 2017

Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains.

Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Distributed Submodular Maximization.

Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause

J. Mach. Learn. Res., 2016

Fast Distributed Submodular Cover: Public-Private Data Summarization.

Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Fast Constrained Submodular Maximization: Personalized Data Summarization.

Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi

Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization.

Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Distributed Submodular Cover: Succinctly Summarizing Massive Data.

Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Lazier Than Lazy Greedy.

Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014

Streaming submodular maximization: massive data summarization on the fly.

Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014

2013

Revenue maximization in social networks through discounting.

Mahmoudreza Babaei, Baharan Mirzasoleiman, Mahdi Jalili, Mohammad Ali Safari

Soc. Netw. Anal. Min., 2013

Distributed Submodular Maximization: Identifying Representative Elements in Massive Data.

Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2011

Reuse-Attack Mitigation in Wireless Sensor Networks.

Hosein Shafiei, Ahmad Khonsari, Baharan Mirzasoleiman, Mohamed Ould-Khaoua

Proceedings of IEEE International Conference on Communications, 2011

2009

Utility Proportional Optimization Flow Control for Overlay Multicast.

Ali Jafari, Hosein Shafiei, Baharan Mirzasoleiman, Ghodrat Sepidnam

Proceedings of the IEEE International Symposium on Parallel and Distributed Processing with Applications, 2009