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Baharan Mirzasoleiman
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2020 – today
- 2024
- [c43]Siddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman:
Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity. AISTATS 2024: 1000-1008 - [c42]Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman:
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. AISTATS 2024: 2953-2961 - [c41]Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman:
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality. ICLR 2024 - [c40]Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman:
Investigating the Benefits of Projection Head for Representation Learning. ICLR 2024 - [c39]Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman:
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift. ICLR 2024 - [c38]Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman, Omid Abari:
NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction. ICML 2024 - [c37]Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman:
Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings. ICML 2024 - [c36]Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman:
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks. ICML 2024 - [i44]Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman, Omid Abari:
A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction. CoRR abs/2403.03241 (2024) - [i43]Yu Yang, Siddhartha Mishra, Jeffrey N. Chiang
, Baharan Mirzasoleiman:
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models. CoRR abs/2403.07384 (2024) - [i42]Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman:
Investigating the Benefits of Projection Head for Representation Learning. CoRR abs/2403.11391 (2024) - [i41]Siddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman:
Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity. CoRR abs/2403.12267 (2024) - [i40]Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman:
Make the Most of Your Data: Changing the Training Data Distribution to Improve In-distribution Generalization Performance. CoRR abs/2404.17768 (2024) - [i39]Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman:
Memory-efficient Training of LLMs with Larger Mini-batches. CoRR abs/2407.19580 (2024) - [i38]Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman:
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks. CoRR abs/2410.02116 (2024) - 2023
- [j3]Junaid Ali
On the Fairness of Time-Critical Influence Maximization in Social Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2875-2886 (2023) - [c35]Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman:
High Probability Bounds for Stochastic Continuous Submodular Maximization. AISTATS 2023: 5958-5979 - [c34]Neha Prakriya
NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training. HotStorage 2023: 8-15 - [c33]Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh:
A Self-supervised Framework for Improved Data-Driven Monitoring of Stress via Multi-Modal Passive Sensing. ICDH 2023: 177-183 - [c32]Siddharth Joshi, Baharan Mirzasoleiman:
Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least. ICML 2023: 15356-15370 - [c31]Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman:
Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression. ICML 2023: 38938-38970 - [c30]Yu Yang, Hao Kang, Baharan Mirzasoleiman:
Towards Sustainable Learning: Coresets for Data-efficient Deep Learning. ICML 2023: 39314-39330 - [c29]Yu Yang, Besmira Nushi, Hamid Palangi, Baharan Mirzasoleiman:
Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning. ICML 2023: 39365-39379 - [c28]Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu:
Robust Learning with Progressive Data Expansion Against Spurious Correlation. NeurIPS 2023 - [c27]Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman:
Robust Contrastive Language-Image Pretraining against Data Poisoning and Backdoor Attacks. NeurIPS 2023 - [i37]Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp, Baharan Mirzasoleiman:
Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization. CoRR abs/2302.00138 (2023) - [i36]Siddharth Joshi, Baharan Mirzasoleiman:
Data-Efficient Contrastive Self-supervised Learning: Easy Examples Contribute the Most. CoRR abs/2302.09195 (2023) - [i35]Wenhan Yang, Baharan Mirzasoleiman:
Contrastive Learning under Heterophily. CoRR abs/2303.06344 (2023) - [i34]Wenhan Yang, Baharan Mirzasoleiman:
Robust Contrastive Language-Image Pretraining against Adversarial Attacks. CoRR abs/2303.06854 (2023) - [i33]Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman:
High Probability Bounds for Stochastic Continuous Submodular Maximization. CoRR abs/2303.11937 (2023) - [i32]Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh:
A Self-supervised Framework for Improved Data-Driven Monitoring of Stress via Multi-modal Passive Sensing. CoRR abs/2303.14267 (2023) - [i31]Yu Yang, Besmira Nushi, Hamid Palangi, Baharan Mirzasoleiman:
Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning. CoRR abs/2304.03916 (2023) - [i30]Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman:
Eliminating Spurious Correlations from Pre-trained Models via Data Mixing. CoRR abs/2305.14521 (2023) - [i29]Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman:
Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression. CoRR abs/2305.16536 (2023) - [i28]Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman:
Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. CoRR abs/2305.18761 (2023) - [i27]Yu Yang, Hao Kang, Baharan Mirzasoleiman:
Towards Sustainable Learning: Coresets for Data-efficient Deep Learning. CoRR abs/2306.01244 (2023) - [i26]Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu:
Robust Learning with Progressive Data Expansion Against Spurious Correlation. CoRR abs/2306.04949 (2023) - [i25]Siddharth Joshi, Yu Yang, Yihao Xue, Wenhan Yang, Baharan Mirzasoleiman:
Towards Mitigating Spurious Correlations in the Wild: A Benchmark & a more Realistic Dataset. CoRR abs/2306.11957 (2023) - [i24]Yuetong Xu, Baharan Mirzasoleiman:
Ordering for Non-Replacement SGD. CoRR abs/2306.15848 (2023) - [i23]Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman:
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift. CoRR abs/2310.04971 (2023) - [i22]Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman:
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks. CoRR abs/2310.05862 (2023) - [i21]Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman:
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality. CoRR abs/2310.06982 (2023) - [i20]Lauren Watson, Eric Gan, Mohan Dantam, Baharan Mirzasoleiman, Rik Sarkar:
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent. CoRR abs/2311.06839 (2023) - 2022
- [c26]Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi
CrossWalk: Fairness-Enhanced Node Representation Learning. AAAI 2022: 11963-11970 - [c25]Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh:
Passive Monitoring of Physiological Precursors of Stress Leveraging Smartwatch Data. BIBM 2022: 2893-2899 - [c24]Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi
On the Fairness of Time-Critical Influence Maximization in Social Networks (Extended Abstract). ICDE 2022: 1541-1542 - [c23]Omead Pooladzandi, David Davini, Baharan Mirzasoleiman:
Adaptive Second Order Coresets for Data-efficient Machine Learning. ICML 2022: 17848-17869 - [c22]Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman:
Investigating Why Contrastive Learning Benefits Robustness against Label Noise. ICML 2022: 24851-24871 - [c21]Yu Yang, Tian Yu Liu, Baharan Mirzasoleiman:
Not All Poisons are Created Equal: Robust Training against Data Poisoning. ICML 2022: 25154-25165 - [c20]Tian Yu Liu, Baharan Mirzasoleiman:
Data-Efficient Augmentation for Training Neural Networks. NeurIPS 2022 - [c19]Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman:
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack. NeurIPS 2022 - [c18]Alexandra M. Porter, Baharan Mirzasoleiman, Jure Leskovec:
Analytical Models for Motifs in Temporal Networks. WWW (Companion Volume) 2022: 903-909 - [i19]Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman:
Investigating Why Contrastive Learning Benefits Robustness Against Label Noise. CoRR abs/2201.12498 (2022) - [i18]Omead Pooladzandi, David Davini, Baharan Mirzasoleiman:
Adaptive Second Order Coresets for Data-efficient Machine Learning. CoRR abs/2207.13887 (2022) - [i17]Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman:
Superior generalization of smaller models in the presence of significant label noise. CoRR abs/2208.08003 (2022) - [i16]Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman:
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks. CoRR abs/2208.10224 (2022) - [i15]Tian Yu Liu, Baharan Mirzasoleiman:
Data-Efficient Augmentation for Training Neural Networks. CoRR abs/2210.08363 (2022) - [i14]Yu Yang, Tian Yu Liu, Baharan Mirzasoleiman:
Not All Poisons are Created Equal: Robust Training against Data Poisoning. CoRR abs/2210.09671 (2022) - 2021
- [i13]KrishnaTeja Killamsetty, Durga Sivasubramanian, Baharan Mirzasoleiman, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer:
GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning. CoRR abs/2103.00123 (2021) - [i12]Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman:
CrossWalk: Fairness-enhanced Node Representation Learning. CoRR abs/2105.02725 (2021) - [i11]Alexandra M. Porter, Baharan Mirzasoleiman, Jure Leskovec:
Analytical Models for Motifs in Temporal Networks: Discovering Trends and Anomalies. CoRR abs/2112.14871 (2021) - 2020
- [c17]Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia:
Selection via Proxy: Efficient Data Selection for Deep Learning. ICLR 2020 - [c16]Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec:
Coresets for Data-efficient Training of Machine Learning Models. ICML 2020: 6950-6960 - [c15]Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec:
Coresets for Robust Training of Deep Neural Networks against Noisy Labels. NeurIPS 2020 - [c14]Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger:
Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples. UAI 2020: 350-359 - [i10]Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec:
Coresets for Robust Training of Neural Networks against Noisy Labels. CoRR abs/2011.07451 (2020)
2010 – 2019
- 2019
- [i9]Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla:
On the Fairness of Time-Critical Influence Maximization in Social Networks. CoRR abs/1905.06618 (2019) - [i8]Saeed Vahidian, Alexander Cloninger, Baharan Mirzasoleiman:
Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization. CoRR abs/1906.01021 (2019) - [i7]Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec:
Data Sketching for Faster Training of Machine Learning Models. CoRR abs/1906.01827 (2019) - [i6]Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia:
Selection Via Proxy: Efficient Data Selection For Deep Learning. CoRR abs/1906.11829 (2019) - 2018
- [c13]Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause:
Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly. AAAI 2018: 1379-1386 - [c12]Elahe Ghalebi, Baharan Mirzasoleiman, Radu Grosu, Jure Leskovec:
Dynamic Network Model from Partial Observations. NeurIPS 2018: 9884-9894 - [i5]Elahe Ghalebi K., Baharan Mirzasoleiman, Radu Grosu, Jure Leskovec:
Dynamic Network Model from Partial Observations. CoRR abs/1805.10616 (2018) - 2017
- [b1]Baharan Mirzasoleiman:
Big Data Summarization Using Submodular Functions. ETH Zurich, Zürich, Switzerland, 2017 - [c11]Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause:
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. AISTATS 2017: 111-120 - [c10]Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause:
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". ICML 2017: 2449-2458 - [i4]Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause:
Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly. CoRR abs/1706.03583 (2017) - 2016
- [j2]Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause:
Distributed Submodular Maximization. J. Mach. Learn. Res. 17: 238:1-238:44 (2016) - [c9]Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi:
Fast Constrained Submodular Maximization: Personalized Data Summarization. ICML 2016: 1358-1367 - [c8]Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer:
Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. ICML 2016: 2207-2216 - [c7]Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi:
Fast Distributed Submodular Cover: Public-Private Data Summarization. NIPS 2016: 3594-3602 - [i3]Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause:
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. CoRR abs/1606.05615 (2016) - 2015
- [c6]Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause:
Lazier Than Lazy Greedy. AAAI 2015: 1812-1818 - [c5]Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause:
Distributed Submodular Cover: Succinctly Summarizing Massive Data. NIPS 2015: 2881-2889 - 2014
- [c4]Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause:
Streaming submodular maximization: massive data summarization on the fly. KDD 2014: 671-680 - [i2]Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause:
Lazier Than Lazy Greedy. CoRR abs/1409.7938 (2014) - [i1]Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause:
Distributed Submodular Maximization. CoRR abs/1411.0541 (2014) - 2013
- [j1]Mahmoudreza Babaei, Baharan Mirzasoleiman, Mahdi Jalili
Revenue maximization in social networks through discounting. Soc. Netw. Anal. Min. 3(4): 1249-1262 (2013) - [c3]Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause:
Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. NIPS 2013: 2049-2057 - 2011
- [c2]Hosein Shafiei
Reuse-Attack Mitigation in Wireless Sensor Networks. ICC 2011: 1-5
2000 – 2009
- 2009
- [c1]Ali Jafari, Hosein Shafiei
Utility Proportional Optimization Flow Control for Overlay Multicast. ISPA 2009: 401-407
Coauthor Index
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last updated on 2024-11-11 22:25 CET by the dblp team
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