Efficient Iterative Semi-supervised Classification on Manifold. - Mehrdad Farajtabar; Hamid R. Rabiee; Amirreza Shaban; Ali Soltani-Farani (ICDM Workshops, 2011)

Manifold Coarse Graining for Online Semi-supervised Learning. - Mehrdad Farajtabar; Amirreza Shaban; Hamid Reza Rabiee; Mohammad H. Rohban (ECML/PKDD (1), 2011)

Online Object Representation Learning and Its Application to Object Tracking. - Amirreza Shaban; Hamid R. Rabiee; Mehrdad Farajtabar; Mohsen Fadaee (AAAI Spring Symposium: Lifelong Machine Learning, 2013)

From Local Similarity to Global Coding: An Application to Image Classification. - Amirreza Shaban; Hamid R. Rabiee; Mehrdad Farajtabar; Marjan Ghazvininejad (CVPR, 2013)

Shaping Social Activity by Incentivizing Users. - Mehrdad Farajtabar; Nan Du 002; Manuel Gomez-Rodriguez; Isabel Valera; Hongyuan Zha; Le Song (NIPS, 2014)

Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades. - Mehrdad Farajtabar; Manuel Gomez-Rodriguez; Mohammad Zamani; Nan Du 002; Hongyuan Zha; Le Song (AISTATS, 2015)

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams. - Nan Du 002; Mehrdad Farajtabar; Amr Ahmed 001; Alexander J. Smola; Le Song (KDD, 2015)

NetCodec: Community Detection from Individual Activities. - Long Q. Tran; Mehrdad Farajtabar; Le Song; Hongyuan Zha (SDM, 2015)

Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Method. - Amirreza Shaban; Mehrdad Farajtabar; Bo Xie 002; Le Song; Byron Boots (UAI, 2015)

Co-evolutionary Dynamics of Information Diffusion and Network Structure. - Mehrdad Farajtabar; Manuel Gomez-Rodriguez; Yichen Wang 001; Shuang Li 002; Hongyuan Zha; Le Song (WWW (Companion Volume), 2015)

A Continuous-time Mutually-Exciting Point Process Framework for Prioritizing Events in Social Media. - Mehrdad Farajtabar; Safoora Yousefi; Long Q. Tran; Le Song; Hongyuan Zha (CoRR, 2015)

Correlated Cascades: Compete or Cooperate. - Ali Zarezade; Ali Khodadadi; Mehrdad Farajtabar; Hamid R. Rabiee; Le Song; Hongyuan Zha (CoRR, 2015)

On the network you keep: analyzing persons of interest using Cliqster. - Saber Shokat Fadaee; Mehrdad Farajtabar; Ravi Sundaram; Javed A. Aslam; Nikos I. Passas (Soc. Netw. Anal. Min., 2015)

Learning Granger Causality for Hawkes Processes. - Hongteng Xu; Mehrdad Farajtabar; Hongyuan Zha (ICML, 2016)

Smart Broadcasting: Do You Want to be Seen? - Mohammad Reza Karimi; Erfan Tavakoli; Mehrdad Farajtabar; Le Song; Manuel Gomez-Rodriguez (KDD, 2016)

Multistage Campaigning in Social Networks. - Mehrdad Farajtabar; Xiaojing Ye; Sahar Harati; Le Song; Hongyuan Zha (NIPS, 2016)

Detecting weak changes in dynamic events over networks. - Shuang Li 002; Yao Xie 002; Mehrdad Farajtabar; Le Song (CoRR, 2016)

Correlated Cascades: Compete or Cooperate. - Ali Zarezade; Ali Khodadadi; Mehrdad Farajtabar; Hamid R. Rabiee; Hongyuan Zha (AAAI, 2017)

Fake News Mitigation via Point Process Based Intervention. - Mehrdad Farajtabar; Jiachen Yang; Xiaojing Ye; Huan Xu; Rakshit Trivedi; Elias B. Khalil; Shuang Li 002; Le Song; Hongyuan Zha (ICML, 2017)

Wasserstein Learning of Deep Generative Point Process Models. - Shuai Xiao 002; Mehrdad Farajtabar; Xiaojing Ye; Junchi Yan; Xiaokang Yang 001; Le Song; Hongyuan Zha (NIPS, 2017)

Distilling Information Reliability and Source Trustworthiness from Digital Traces. - Behzad Tabibian; Isabel Valera; Mehrdad Farajtabar; Le Song; Bernhard Schölkopf; Manuel Gomez-Rodriguez (WWW, 2017)

Wasserstein Learning of Deep Generative Point Process Models. - Shuai Xiao 002; Mehrdad Farajtabar; Xiaojing Ye; Junchi Yan; Le Song; Hongyuan Zha (CoRR, 2017)

Joint Modeling of Event Sequence and Time Series with Attentional Twin Recurrent Neural Networks. - Shuai Xiao 002; Junchi Yan; Mehrdad Farajtabar; Le Song; Xiaokang Yang 001; Hongyuan Zha (CoRR, 2017)

Hawkes Processes for Invasive Species Modeling and Management. - Amrita Gupta; Mehrdad Farajtabar; Bistra Dilkina; Hongyuan Zha (CoRR, 2017)

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution. - Mehrdad Farajtabar; Yichen Wang 001; Manuel Gomez-Rodriguez; Shuang Li 002; Hongyuan Zha; Le Song (J. Mach. Learn. Res., 2017)

Detecting Changes in Dynamic Events Over Networks. - Shuang Li 002; Yao Xie 002; Mehrdad Farajtabar; Apurv Verma; Le Song (IEEE Trans. Signal Inf. Process. over Networks, 2017)

Learning Conditional Generative Models for Temporal Point Processes. - Shuai Xiao 002; Hongteng Xu; Junchi Yan; Mehrdad Farajtabar; Xiaokang Yang 001; Le Song; Hongyuan Zha (AAAI, 2018)

More Robust Doubly Robust Off-policy Evaluation. - Mehrdad Farajtabar; Yinlam Chow; Mohammad Ghavamzadeh (ICML, 2018)

Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management. - Amrita Gupta; Mehrdad Farajtabar; Bistra Dilkina; Hongyuan Zha (IJCAI, 2018)

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution. - Mehrdad Farajtabar; Manuel Gomez-Rodriguez; Yichen Wang 001; Shuang Li 002; Hongyuan Zha; Le Song (WWW (Companion Volume), 2018)

Representation Learning over Dynamic Graphs. - Rakshit Trivedi; Mehrdad Farajtabar; Prasenjeet Biswal; Hongyuan Zha (CoRR, 2018)

Point process modeling and optimization of social networks. - Mehrdad Farajtabar (2018)

Cross-View Policy Learning for Street Navigation. - Ang Li; Huiyi Hu; Piotr Mirowski; Mehrdad Farajtabar (ICCV, 2019)

DyRep: Learning Representations over Dynamic Graphs. - Rakshit Trivedi; Mehrdad Farajtabar; Prasenjeet Biswal; Hongyuan Zha (ICLR (Poster), 2019)

Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher. - Seyed-Iman Mirzadeh; Mehrdad Farajtabar; Ang Li; Hassan Ghasemzadeh 001 (CoRR, 2019)

Modeling behaviors and lifestyle with online and social data for predicting and analyzing sleep and exercise quality. - Mehrdad Farajtabar; Emre Kiciman; Girish Nathan; Ryen W. White (Int. J. Data Sci. Anal., 2019)

Learning Time Series Associated Event Sequences With Recurrent Point Process Networks. - Shuai Xiao 002; Junchi Yan; Mehrdad Farajtabar; Le Song; Xiaokang Yang 001; Hongyuan Zha (IEEE Trans. Neural Networks Learn. Syst., 2019)

Improved Knowledge Distillation via Teacher Assistant. - Seyed-Iman Mirzadeh; Mehrdad Farajtabar; Ang Li; Nir Levine; Akihiro Matsukawa; Hassan Ghasemzadeh 001 (AAAI, 2020)

Orthogonal Gradient Descent for Continual Learning. - Mehrdad Farajtabar; Navid Azizan; Alex Mott; Ang Li (AISTATS, 2020)

Dropout as an Implicit Gating Mechanism For Continual Learning. - Seyed-Iman Mirzadeh; Mehrdad Farajtabar; Hassan Ghasemzadeh 001 (CVPR Workshops, 2020)

A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs. - Nevena Lazic; Dong Yin; Mehrdad Farajtabar; Nir Levine; Dilan Görür; Chris Harris 001; Dale Schuurmans (NeurIPS, 2020)

Understanding the Role of Training Regimes in Continual Learning. - Seyed-Iman Mirzadeh; Mehrdad Farajtabar; Razvan Pascanu; Hassan Ghasemzadeh 001 (NeurIPS, 2020)

Self-Distillation Amplifies Regularization in Hilbert Space. - Hossein Mobahi; Mehrdad Farajtabar; Peter L. Bartlett (NeurIPS, 2020)

Learning to Incentivize Other Learning Agents. - Jiachen Yang; Ang Li; Mehrdad Farajtabar; Peter Sunehag; Edward Hughes 001; Hongyuan Zha (NeurIPS, 2020)

SOLA: Continual Learning with Second-Order Loss Approximation. - Dong Yin; Mehrdad Farajtabar; Ang Li (CoRR, 2020)

The Effectiveness of Memory Replay in Large Scale Continual Learning. - Yogesh Balaji; Mehrdad Farajtabar; Dong Yin; Alex Mott; Ang Li (CoRR, 2020)

Balance Regularized Neural Network Models for Causal Effect Estimation. - Mehrdad Farajtabar; Andrew Lee; Yuanjian Feng; Vishal Gupta; Peter Dolan; Harish Chandran; Martin Szummer (CoRR, 2020)

Recurrent Poisson Factorization for Temporal Recommendation. - Seyed Abbas Hosseini; Ali Khodadadi; Keivan Alizadeh; Ali Arabzadeh; Mehrdad Farajtabar; Hongyuan Zha; Hamid R. Rabiee (IEEE Trans. Knowl. Data Eng., 2020)

Linear Mode Connectivity in Multitask and Continual Learning. - Seyed-Iman Mirzadeh; Mehrdad Farajtabar; Dilan Görür; Razvan Pascanu; Hassan Ghasemzadeh 001 (ICLR, 2021)

Task-agnostic Continual Learning with Hybrid Probabilistic Models. - Polina Kirichenko; Mehrdad Farajtabar; Dushyant Rao; Balaji Lakshminarayanan; Nir Levine; Ang Li; Huiyi Hu; Andrew Gordon Wilson; Razvan Pascanu (CoRR, 2021)

Wide Neural Networks Forget Less Catastrophically. - Seyed-Iman Mirzadeh; Arslan Chaudhry; Huiyi Hu; Razvan Pascanu; Dilan Görür; Mehrdad Farajtabar (CoRR, 2021)

Wide Neural Networks Forget Less Catastrophically. - Seyed-Iman Mirzadeh; Arslan Chaudhry; Dong Yin; Huiyi Hu; Razvan Pascanu; Dilan Görür; Mehrdad Farajtabar (ICML, 2022)

Architecture Matters in Continual Learning. - Seyed-Iman Mirzadeh; Arslan Chaudhry; Dong Yin; Timothy Nguyen; Razvan Pascanu; Dilan Görür; Mehrdad Farajtabar (CoRR, 2022)

Efficient Continual Learning Ensembles in Neural Network Subspaces. - Thang Doan; Seyed-Iman Mirzadeh; Joelle Pineau; Mehrdad Farajtabar (CoRR, 2022)

An empirical study of implicit regularization in deep offline RL. - Çaglar Gülçehre; Srivatsan Srinivasan; Jakub Sygnowski; Georg Ostrovski; Mehrdad Farajtabar; Matthew Hoffman 002; Razvan Pascanu; Arnaud Doucet (Trans. Mach. Learn. Res., 2022)

Continual Learning Beyond a Single Model. - Thang Doan; Seyed-Iman Mirzadeh; Mehrdad Farajtabar (CoLLAs, 2023)

Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement. - Fartash Faghri; Hadi Pouransari; Sachin Mehta; Mehrdad Farajtabar; Ali Farhadi; Mohammad Rastegari; Oncel Tuzel (ICCV, 2023)

On the Efficacy of Multi-scale Data Samplers for Vision Applications. - Elvis Nunez; Thomas Merth; Anish Prabhu; Mehrdad Farajtabar; Mohammad Rastegari; Sachin Mehta; Maxwell Horton (CoRR, 2023)

Label-efficient Training of Small Task-specific Models by Leveraging Vision Foundation Models. - Raviteja Vemulapalli; Hadi Pouransari; Fartash Faghri; Sachin Mehta; Mehrdad Farajtabar; Mohammad Rastegari; Oncel Tuzel (CoRR, 2023)

Weight subcloning: direct initialization of transformers using larger pretrained ones. - Mohammad Samragh; Mehrdad Farajtabar; Sachin Mehta; Raviteja Vemulapalli; Fartash Faghri; Devang Naik; Oncel Tuzel; Mohammad Rastegari (CoRR, 2023)

LLM in a flash: Efficient Large Language Model Inference with Limited Memory. - Keivan Alizadeh; Iman Mirzadeh; Dmitry Belenko; Karen Khatamifard; Minsik Cho; Carlo C. del Mundo; Mohammad Rastegari; Mehrdad Farajtabar (CoRR, 2023)

Guest Editorial Robust Learning of Spatio-Temporal Point Processes: Modeling, Algorithm, and Applications. - Junchi Yan; Hongteng Xu; Liangda Li; Mehrdad Farajtabar; Xiaokang Yang 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

LLM in a flash: Efficient Large Language Model Inference with Limited Memory. - Keivan Alizadeh; Iman Mirzadeh; Dmitry Belenko; S. Khatamifard; Minsik Cho; Carlo C. del Mundo; Mohammad Rastegari; Mehrdad Farajtabar (ACL (1), 2024)

SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding. - Haoxiang Wang 003; Pavan Kumar Anasosalu Vasu; Fartash Faghri; Raviteja Vemulapalli; Mehrdad Farajtabar; Sachin Mehta; Mohammad Rastegari; Oncel Tuzel; Hadi Pouransari (CVPR Workshops, 2024)

Duo-LLM: A Framework for Studying Adaptive Computation in Large Language Models. - Keivan Alizadeh-Vahid; Seyed-Iman Mirzadeh; Hooman Shahrkokhi; Dmitry Belenko; Frank Sun; Minsik Cho; Mohammad Hossein Sekhavat; Moin Nabi; Mehrdad Farajtabar (ENLSP, 2024)

Computational Bottlenecks of Training Small-scale Large Language Models. - Saleh Ashkboos; Seyed Iman Mirzadeh; Keivan Alizadeh-Vahid; Mohammad Hossein Sekhavat; Moin Nabi; Mehrdad Farajtabar; Fartash Faghri (ENLSP, 2024)

Scaling Smart: Accelerating Large Language Model Pre-Training with Small Model Initialization. - Mohammad Samragh; Seyed-Iman Mirzadeh; Keivan Alizadeh-Vahid; Fartash Faghri; Minsik Cho; Moin Nabi; Devang Naik; Mehrdad Farajtabar (ENLSP, 2024)

TiC-CLIP: Continual Training of CLIP Models. - Saurabh Garg; Mehrdad Farajtabar; Hadi Pouransari; Raviteja Vemulapalli; Sachin Mehta; Oncel Tuzel; Vaishaal Shankar; Fartash Faghri (ICLR, 2024)

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models. - Iman Mirzadeh; Keivan Alizadeh-Vahid; Sachin Mehta; Carlo C. del Mundo; Oncel Tuzel; Golnoosh Samei; Mohammad Rastegari; Mehrdad Farajtabar (ICLR, 2024)

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models. - Raviteja Vemulapalli; Hadi Pouransari; Fartash Faghri; Sachin Mehta; Mehrdad Farajtabar; Mohammad Rastegari; Oncel Tuzel (ICML, 2024)

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data. - Sachin Mehta; Maxwell Horton; Fartash Faghri; Mohammad Hossein Sekhavat; Mahyar Najibi; Mehrdad Farajtabar; Oncel Tuzel; Mohammad Rastegari (CoRR, 2024)

Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization. - Mohammad Samragh; Iman Mirzadeh; Keivan Alizadeh-Vahid; Fartash Faghri; Minsik Cho; Moin Nabi; Devang Naik; Mehrdad Farajtabar (CoRR, 2024)

Duo-LLM: A Framework for Studying Adaptive Computation in Large Language Models. - Keivan Alizadeh; Iman Mirzadeh; Hooman Shahrokhi; Dmitry Belenko; Frank Sun; Minsik Cho; Mohammad Hossein Sekhavat; Moin Nabi; Mehrdad Farajtabar (CoRR, 2024)

Computational Bottlenecks of Training Small-scale Large Language Models. - Saleh Ashkboos; Iman Mirzadeh; Keivan Alizadeh; Mohammad Hossein Sekhavat; Moin Nabi; Mehrdad Farajtabar; Fartash Faghri (CoRR, 2024)

SALSA: Soup-based Alignment Learning for Stronger Adaptation in RLHF. - Atoosa Malemir Chegini; Hamid Kazemi; Iman Mirzadeh; Dong Yin; Maxwell Horton; Moin Nabi; Mehrdad Farajtabar; Keivan Alizadeh (CoRR, 2024)

CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement. - Mohammadreza Salehi; Mehrdad Farajtabar; Maxwell Horton; Fartash Faghri; Hadi Pouransari; Raviteja Vemulapalli; Oncel Tuzel; Ali Farhadi; Mohammad Rastegari; Sachin Mehta (Trans. Mach. Learn. Res., 2024)

TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining. - Jeffrey Li; Mohammadreza Armandpour; Iman Mirzadeh; Sachin Mehta; Vaishaal Shankar; Raviteja Vemulapalli; Samy Bengio; Oncel Tuzel; Mehrdad Farajtabar; Hadi Pouransari; Fartash Faghri (ACL (1), 2025)

GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models. - Iman Mirzadeh; Keivan Alizadeh; Hooman Shahrokhi; Oncel Tuzel; Samy Bengio; Mehrdad Farajtabar (ICLR, 2025)

From Dense to Dynamic: Token-Difficulty Driven MoEfication of Pre-Trained LLMs. - Kumari Nishu; Sachin Mehta; Samira Abnar; Mehrdad Farajtabar; Maxwell Horton; Mahyar Najibi; Moin Nabi; Minsik Cho; Devang Naik (CoRR, 2025)

Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting. - Chen Huang 001; Skyler Seto; Hadi Pouransari; Mehrdad Farajtabar; Raviteja Vemulapalli; Fartash Faghri; Oncel Tuzel; Barry-John Theobald; Joshua M. Susskind (CoRR, 2025)

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity. - Parshin Shojaee; Iman Mirzadeh; Keivan Alizadeh; Maxwell Horton; Samy Bengio; Mehrdad Farajtabar (CoRR, 2025)

RL for Reasoning by Adaptively Revealing Rationales. - Mohammad Hossein Amani; Aryo Lotfi; Nicolas Mario Baldwin; Samy Bengio; Mehrdad Farajtabar; Emmanuel Abbe; Robert West 001 (CoRR, 2025)

Your LLM Knows the Future: Uncovering Its Multi-Token Prediction Potential. - Mohammad Samragh; Arnav Kundu; David Harrison; Kumari Nishu; Devang Naik; Minsik Cho; Mehrdad Farajtabar (CoRR, 2025)