Baharan Mirzasoleiman

117 papers A* 35A 7C 1Journal 64Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond What Seems Necessary: Hidden Gains from Scaling Training-Time Reasoning Length under Outcome Supervision. CoRR Yihao Xue, Allan Zhang, Jianhao Huang, Amit Sahai, Baharan Mirzasoleiman
2026	J	`jnl`	Data Distribution as a Lever for Guiding Optimizers Toward Superior Generalization in LLMs. CoRR Tushaar Gangavarapu, Jiping Li, Christopher Vattheuer, Zhangyang Wang, Baharan Mirzasoleiman
2026	J	`jnl`	Theoretical Perspectives on Data Quality and Synergistic Effects in Pre- and Post-Training Reasoning Models. CoRR Adel Javanmard, Baharan Mirzasoleiman, Vahab Mirrokni
2026	J	`jnl`	Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from k-Parity. CoRR Jianhao Huang, Baharan Mirzasoleiman
2025	—	`conf`	Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity. ACL (Findings) Dang Nguyen, Ali Payani, Baharan Mirzasoleiman
2025	J	`jnl`	Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity. CoRR Dang Nguyen, Ali Payani, Baharan Mirzasoleiman
2025	J	`jnl`	Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap. CoRR Wenhan Yang, Spencer Stice, Ali Payani, Baharan Mirzasoleiman
2025	J	`jnl`	DD-Ranking: Rethinking the Evaluation of Dataset Distillation. CoRR Zekai Li, Xinhao Zhong, Samir Khaki, Zhiyuan Liang, Yuhao Zhou, Mingjia Shi, Ziqiao Wang, Xuanlei Zhao, Wangbo Zhao, Ziheng Qin, Mengxuan Wu, Pengfei Zhou, Haonan Wang, David Junhao Zhang, Jia-Wei Liu, Shaobo Wang, Dai Liu, Linfeng Zhang, Guang Li, Kun Wang, Zheng Zhu, Zhiheng Ma, Joey Tianyi Zhou, Jiancheng Lv, Yaochu Jin, Peihao Wang, Kaipeng Zhang, Lingjuan Lyu, Yiran Huang, Zeynep Akata, Zhiwei Deng, Xindi Wu, George Cazenavette, Yuzhang Shang, Justin Cui, Jindong Gu, Qian Zheng, Hao Ye, Shuo Wang, Xiaobo Wang, Yan Yan, Angela Yao, Mike Zheng Shou, Tianlong Chen, Hakan Bilen, Baharan Mirzasoleiman, Manolis Kellis, Konstantinos N. Plataniotis, Zhangyang Wang, Bo Zhao, Yang You, Kai Wang
2025	J	`jnl`	Data Selection for Fine-tuning Vision Language Models via Cross Modal Alignment Trajectories. CoRR Nilay Naharas, Dang Nguyen, Neslihan Bulut, MohammadHossein Bateni, Vahab Mirrokni, Baharan Mirzasoleiman
2025	A*	`conf`	Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks. ICLR Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
2025	J	`jnl`	Do We Need All the Synthetic Data? Towards Targeted Synthetic Image Augmentation via Diffusion Models. CoRR Dang Nguyen, Jiping Li, JingHao Zheng, Baharan Mirzasoleiman
2025	J	`jnl`	LoRA is All You Need for Safety Alignment of Reasoning LLMs. CoRR Yihao Xue, Baharan Mirzasoleiman
2025	J	`jnl`	MM-GEN: Enhancing Task Performance Through Targeted Multimodal Data Curation. CoRR Siddharth Joshi, Besmira Nushi, Vidhisha Balachandran, Varun Chandrasekaran, Vibhav Vineet, Neel Joshi, Baharan Mirzasoleiman
2025	J	`jnl`	MM-GEN: Principled and Generalizable Data Curation for Enhancing Task Performance in VLMs. J. Data-centric Mach. Learn. Res. Siddharth Joshi, Besmira Nushi, Vidhisha Balachandran, Varun Chandrasekaran, Vibhav Vineet, Neel Joshi, Baharan Mirzasoleiman
2025	A*	`conf`	Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures. ICLR Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman
2025	J	`jnl`	Occam's Razor for SSL: Memory-Efficient Parametric Instance Discrimination. Trans. Mach. Learn. Res. Eric Gan, Patrik Reizinger, Alice Bizeul, Attila Juhos, Mark Ibrahim, Randall Balestriero, David A. Klindt, Wieland Brendel, Baharan Mirzasoleiman
2025	A*	`conf`	Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions. ICML Yihao Xue, Jiping Li, Baharan Mirzasoleiman
2025	J	`jnl`	Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions. CoRR Yihao Xue, Jiping Li, Baharan Mirzasoleiman
2025	A*	`conf`	Synthetic Text Generation for Training Large Language Models via Gradient Matching. ICML Dang Nguyen, Zeman Li, MohammadHossein Bateni, Vahab Mirrokni, Meisam Razaviyayn, Baharan Mirzasoleiman
2025	J	`jnl`	Synthetic Text Generation for Training Large Language Models via Gradient Matching. CoRR Dang Nguyen, Zeman Li, MohammadHossein Bateni, Vahab Mirrokni, Meisam Razaviyayn, Baharan Mirzasoleiman
2025	J	`jnl`	Understanding the Role of Training Data in Test-Time Scaling. CoRR Adel Javanmard, Baharan Mirzasoleiman, Vahab Mirrokni
2025	J	`jnl`	Verify when Uncertain: Beyond Self-Consistency in Black Box Hallucination Detection. CoRR Yihao Xue, Kristjan H. Greenewald, Youssef Mroueh, Baharan Mirzasoleiman
2024	J	`jnl`	A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction. CoRR Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman, Omid Abari
2024	A*	`conf`	Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks. ICML Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman
2024	A*	`conf`	Changing the Training Data Distribution to Reduce Simplicity Bias Improves In-distribution Generalization. NeurIPS Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman
2024	A*	`conf`	Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality. ICLR Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman
2024	A	`conf`	Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity. AISTATS Siddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman
2024	J	`jnl`	Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity. CoRR Siddharth Joshi, Arnav Jain, Ali Payani, Baharan Mirzasoleiman
2024	J	`jnl`	Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks. CoRR Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
2024	A*	`conf`	Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings. ICML Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman
2024	A	`conf`	Graph Contrastive Learning under Heterophily via Graph Filters. UAI Wenhan Yang, Baharan Mirzasoleiman
2024	A	`conf`	Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. AISTATS Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman
2024	A*	`conf`	Investigating the Benefits of Projection Head for Representation Learning. ICLR Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman
2024	J	`jnl`	Investigating the Benefits of Projection Head for Representation Learning. CoRR Yihao Xue, Eric Gan, Jiayi Ni, Siddharth Joshi, Baharan Mirzasoleiman
2024	A	`conf`	Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise. UAI Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
2024	J	`jnl`	Make the Most of Your Data: Changing the Training Data Distribution to Improve In-distribution Generalization Performance. CoRR Dang Nguyen, Paymon Haddad, Eric Gan, Baharan Mirzasoleiman
2024	J	`jnl`	Memory-efficient Training of LLMs with Larger Mini-batches. CoRR Dang Nguyen, Wenhan Yang, Rathul Anand, Yu Yang, Baharan Mirzasoleiman
2024	A*	`conf`	NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction. ICML Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman, Omid Abari
2024	A*	`conf`	SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models. NeurIPS Yu Yang, Siddhartha Mishra, Jeffrey N. Chiang, Baharan Mirzasoleiman
2024	J	`jnl`	SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models. CoRR Yu Yang, Siddhartha Mishra, Jeffrey N. Chiang, Baharan Mirzasoleiman
2024	A*	`conf`	Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift. ICLR Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman
2023	—	`conf`	A Self-supervised Framework for Improved Data-Driven Monitoring of Stress via Multi-Modal Passive Sensing. ICDH Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh
2023	J	`jnl`	A Self-supervised Framework for Improved Data-Driven Monitoring of Stress via Multi-modal Passive Sensing. CoRR Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh
2023	J	`jnl`	Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks. CoRR Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman
2023	J	`jnl`	Contrastive Learning under Heterophily. CoRR Wenhan Yang, Baharan Mirzasoleiman
2023	J	`jnl`	Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality. CoRR Xuxi Chen, Yu Yang, Zhangyang Wang, Baharan Mirzasoleiman
2023	J	`jnl`	Data-Efficient Contrastive Self-supervised Learning: Easy Examples Contribute the Most. CoRR Siddharth Joshi, Baharan Mirzasoleiman
2023	A*	`conf`	Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least. ICML Siddharth Joshi, Baharan Mirzasoleiman
2023	J	`jnl`	Eliminating Spurious Correlations from Pre-trained Models via Data Mixing. CoRR Yihao Xue, Ali Payani, Yu Yang, Baharan Mirzasoleiman
2023	J	`jnl`	Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization. CoRR Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp, Baharan Mirzasoleiman
2023	A	`conf`	High Probability Bounds for Stochastic Continuous Submodular Maximization. AISTATS Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman
2023	J	`jnl`	High Probability Bounds for Stochastic Continuous Submodular Maximization. CoRR Evan Becker, Jingdong Gao, Ted Zadouri, Baharan Mirzasoleiman
2023	J	`jnl`	Identifying Spurious Biases Early in Training through the Lens of Simplicity Bias. CoRR Yu Yang, Eric Gan, Gintare Karolina Dziugaite, Baharan Mirzasoleiman
2023	J	`jnl`	Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent. CoRR Lauren Watson, Eric Gan, Mohan Dantam, Baharan Mirzasoleiman, Rik Sarkar
2023	A*	`conf`	Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning. ICML Yu Yang, Besmira Nushi, Hamid Palangi, Baharan Mirzasoleiman
2023	J	`jnl`	Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning. CoRR Yu Yang, Besmira Nushi, Hamid Palangi, Baharan Mirzasoleiman
2023	—	`conf`	NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training. HotStorage Neha Prakriya, Yu Yang, Baharan Mirzasoleiman, Cho-Jui Hsieh, Jason Cong
2023	J	`jnl`	On the Fairness of Time-Critical Influence Maximization in Social Networks. IEEE Trans. Knowl. Data Eng. Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla
2023	J	`jnl`	Ordering for Non-Replacement SGD. CoRR Yuetong Xu, Baharan Mirzasoleiman
2023	J	`jnl`	Robust Contrastive Language-Image Pretraining against Adversarial Attacks. CoRR Wenhan Yang, Baharan Mirzasoleiman
2023	A*	`conf`	Robust Contrastive Language-Image Pretraining against Data Poisoning and Backdoor Attacks. NeurIPS Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman
2023	A*	`conf`	Robust Learning with Progressive Data Expansion Against Spurious Correlation. NeurIPS Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu
2023	J	`jnl`	Robust Learning with Progressive Data Expansion Against Spurious Correlation. CoRR Yihe Deng, Yu Yang, Baharan Mirzasoleiman, Quanquan Gu
2023	J	`jnl`	Towards Mitigating Spurious Correlations in the Wild: A Benchmark & a more Realistic Dataset. CoRR Siddharth Joshi, Yu Yang, Yihao Xue, Wenhan Yang, Baharan Mirzasoleiman
2023	A*	`conf`	Towards Sustainable Learning: Coresets for Data-efficient Deep Learning. ICML Yu Yang, Hao Kang, Baharan Mirzasoleiman
2023	J	`jnl`	Towards Sustainable Learning: Coresets for Data-efficient Deep Learning. CoRR Yu Yang, Hao Kang, Baharan Mirzasoleiman
2023	J	`jnl`	Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift. CoRR Yihao Xue, Siddharth Joshi, Dang Nguyen, Baharan Mirzasoleiman
2023	A*	`conf`	Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression. ICML Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman
2023	J	`jnl`	Which Features are Learnt by Contrastive Learning? On the Role of Simplicity Bias in Class Collapse and Feature Suppression. CoRR Yihao Xue, Siddharth Joshi, Eric Gan, Pin-Yu Chen, Baharan Mirzasoleiman
2022	A*	`conf`	Adaptive Second Order Coresets for Data-efficient Machine Learning. ICML Omead Pooladzandi, David Davini, Baharan Mirzasoleiman
2022	J	`jnl`	Adaptive Second Order Coresets for Data-efficient Machine Learning. CoRR Omead Pooladzandi, David Davini, Baharan Mirzasoleiman
2022	—	`conf`	Analytical Models for Motifs in Temporal Networks. WWW (Companion Volume) Alexandra M. Porter, Baharan Mirzasoleiman, Jure Leskovec
2022	A*	`conf`	CrossWalk: Fairness-Enhanced Node Representation Learning. AAAI Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman
2022	A*	`conf`	Data-Efficient Augmentation for Training Neural Networks. NeurIPS Tian Yu Liu, Baharan Mirzasoleiman
2022	J	`jnl`	Data-Efficient Augmentation for Training Neural Networks. CoRR Tian Yu Liu, Baharan Mirzasoleiman
2022	A*	`conf`	Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attack. NeurIPS Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman
2022	J	`jnl`	Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks. CoRR Tian Yu Liu, Yu Yang, Baharan Mirzasoleiman
2022	J	`jnl`	Investigating Why Contrastive Learning Benefits Robustness Against Label Noise. CoRR Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
2022	A*	`conf`	Investigating Why Contrastive Learning Benefits Robustness against Label Noise. ICML Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
2022	A*	`conf`	Not All Poisons are Created Equal: Robust Training against Data Poisoning. ICML Yu Yang, Tian Yu Liu, Baharan Mirzasoleiman
2022	J	`jnl`	Not All Poisons are Created Equal: Robust Training against Data Poisoning. CoRR Yu Yang, Tian Yu Liu, Baharan Mirzasoleiman
2022	A*	`conf`	On the Fairness of Time-Critical Influence Maximization in Social Networks (Extended Abstract). ICDE Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla
2022	—	`conf`	Passive Monitoring of Physiological Precursors of Stress Leveraging Smartwatch Data. BIBM Shayan Fazeli, Lionel M. Levine, Mehrab Beikzadeh, Baharan Mirzasoleiman, Bita Zadeh, Tara Peris, Majid Sarrafzadeh
2022	J	`jnl`	Superior generalization of smaller models in the presence of significant label noise. CoRR Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
2021	J	`jnl`	Analytical Models for Motifs in Temporal Networks: Discovering Trends and Anomalies. CoRR Alexandra M. Porter, Baharan Mirzasoleiman, Jure Leskovec
2021	J	`jnl`	CrossWalk: Fairness-enhanced Node Representation Learning. CoRR Ahmad Khajehnejad, Moein Khajehnejad, Mahmoudreza Babaei, Krishna P. Gummadi, Adrian Weller, Baharan Mirzasoleiman
2021	J	`jnl`	GRAD-MATCH: A Gradient Matching Based Data Subset Selection for Efficient Learning. CoRR Krishnateja Killamsetty, Durga Sivasubramanian, Baharan Mirzasoleiman, Ganesh Ramakrishnan, Abir De, Rishabh K. Iyer
2020	A*	`conf`	Coresets for Data-efficient Training of Machine Learning Models. ICML Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec
2020	A	`conf`	Coresets for Estimating Means and Mean Square Error with Limited Greedy Samples. UAI Saeed Vahidian, Baharan Mirzasoleiman, Alexander Cloninger
2020	A*	`conf`	Coresets for Robust Training of Deep Neural Networks against Noisy Labels. NeurIPS Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec
2020	J	`jnl`	Coresets for Robust Training of Neural Networks against Noisy Labels. CoRR Baharan Mirzasoleiman, Kaidi Cao, Jure Leskovec
2020	A*	`conf`	Selection via Proxy: Efficient Data Selection for Deep Learning. ICLR Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia
2019	J	`jnl`	Data Sampling for Graph Based Unsupervised Learning: Convex and Greedy Optimization. CoRR Saeed Vahidian, Alexander Cloninger, Baharan Mirzasoleiman
2019	J	`jnl`	Data Sketching for Faster Training of Machine Learning Models. CoRR Baharan Mirzasoleiman, Jeff A. Bilmes, Jure Leskovec
2019	J	`jnl`	On the Fairness of Time-Critical Influence Maximization in Social Networks. CoRR Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla
2019	J	`jnl`	Selection Via Proxy: Efficient Data Selection For Deep Learning. CoRR Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia
2018	A*	`conf`	Dynamic Network Model from Partial Observations. NeurIPS Elahe Ghalebi, Baharan Mirzasoleiman, Radu Grosu, Jure Leskovec
2018	J	`jnl`	Dynamic Network Model from Partial Observations. CoRR Elahe Ghalebi K., Baharan Mirzasoleiman, Radu Grosu, Jure Leskovec
2018	A*	`conf`	Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly. AAAI Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause
2017	—	`—`	Big Data Summarization Using Submodular Functions. Baharan Mirzasoleiman
2017	A*	`conf`	Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". ICML Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause
2017	A	`conf`	Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. AISTATS Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause
2017	J	`jnl`	Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly. CoRR Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause
2016	J	`jnl`	Distributed Submodular Maximization. J. Mach. Learn. Res. Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2016	A*	`conf`	Fast Constrained Submodular Maximization: Personalized Data Summarization. ICML Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi
2016	—	`conf`	Fast Distributed Submodular Cover: Public-Private Data Summarization. NIPS Baharan Mirzasoleiman, Morteza Zadimoghaddam, Amin Karbasi
2016	J	`jnl`	Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. CoRR Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause
2016	A*	`conf`	Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. ICML Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause, Yaron Singer
2015	—	`conf`	Distributed Submodular Cover: Succinctly Summarizing Massive Data. NIPS Baharan Mirzasoleiman, Amin Karbasi, Ashwinkumar Badanidiyuru, Andreas Krause
2015	A*	`conf`	Lazier Than Lazy Greedy. AAAI Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause
2014	J	`jnl`	Distributed Submodular Maximization. CoRR Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2014	J	`jnl`	Lazier Than Lazy Greedy. CoRR Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi, Jan Vondrák, Andreas Krause
2014	A*	`conf`	Streaming submodular maximization: massive data summarization on the fly. KDD Ashwinkumar Badanidiyuru, Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause
2013	—	`conf`	Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. NIPS Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar, Andreas Krause
2013	J	`jnl`	Revenue maximization in social networks through discounting. Soc. Netw. Anal. Min. Mahmoudreza Babaei, Baharan Mirzasoleiman, Mahdi Jalili, Mohammad Ali Safari
2011	—	`conf`	Reuse-Attack Mitigation in Wireless Sensor Networks. ICC Hosein Shafiei, Ahmad Khonsari, Baharan Mirzasoleiman, Mohamed Ould-Khaoua
2009	C	`conf`	Utility Proportional Optimization Flow Control for Overlay Multicast. ISPA Ali Jafari, Hosein Shafiei, Baharan Mirzasoleiman, Ghodrat Sepidnam