Mehrdad Farajtabar

Orcid: 0000-0002-5510-518X

According to our database1, Mehrdad Farajtabar authored at least 74 papers between 2011 and 2024.

Collaborative distances:

Timeline

2012
2014
2016
2018
2020
2022
2024
0
5
10
7
5
3
2
4
3
1
5
1
3
5
2
1
1
7
2
4
4
3
5
1
2
2
1

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement.
Trans. Mach. Learn. Res., 2024

SALSA: Soup-based Alignment Learning for Stronger Adaptation in RLHF.
CoRR, 2024

Computational Bottlenecks of Training Small-scale Large Language Models.
CoRR, 2024

Duo-LLM: A Framework for Studying Adaptive Computation in Large Language Models.
CoRR, 2024

GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.
CoRR, 2024

Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization.
CoRR, 2024

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data.
CoRR, 2024

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

TiC-CLIP: Continual Training of CLIP Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

LLM in a flash: Efficient Large Language Model Inference with Limited Memory.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Guest Editorial Robust Learning of Spatio-Temporal Point Processes: Modeling, Algorithm, and Applications.
IEEE Trans. Neural Networks Learn. Syst., April, 2023

LLM in a flash: Efficient Large Language Model Inference with Limited Memory.
CoRR, 2023

Weight subcloning: direct initialization of transformers using larger pretrained ones.
CoRR, 2023

Label-efficient Training of Small Task-specific Models by Leveraging Vision Foundation Models.
CoRR, 2023

On the Efficacy of Multi-scale Data Samplers for Vision Applications.
CoRR, 2023

Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Continual Learning Beyond a Single Model.
Proceedings of the Conference on Lifelong Learning Agents, 2023

2022
An empirical study of implicit regularization in deep offline RL.
Trans. Mach. Learn. Res., 2022

Efficient Continual Learning Ensembles in Neural Network Subspaces.
CoRR, 2022

Architecture Matters in Continual Learning.
CoRR, 2022

Wide Neural Networks Forget Less Catastrophically.
Proceedings of the International Conference on Machine Learning, 2022

2021
Wide Neural Networks Forget Less Catastrophically.
CoRR, 2021

Task-agnostic Continual Learning with Hybrid Probabilistic Models.
CoRR, 2021

Linear Mode Connectivity in Multitask and Continual Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Recurrent Poisson Factorization for Temporal Recommendation.
IEEE Trans. Knowl. Data Eng., 2020

Balance Regularized Neural Network Models for Causal Effect Estimation.
CoRR, 2020

The Effectiveness of Memory Replay in Large Scale Continual Learning.
CoRR, 2020

SOLA: Continual Learning with Second-Order Loss Approximation.
CoRR, 2020

Learning to Incentivize Other Learning Agents.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Self-Distillation Amplifies Regularization in Hilbert Space.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Understanding the Role of Training Regimes in Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Maximum-Entropy Approach to Off-Policy Evaluation in Average-Reward MDPs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Dropout as an Implicit Gating Mechanism For Continual Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Orthogonal Gradient Descent for Continual Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Improved Knowledge Distillation via Teacher Assistant.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Learning Time Series Associated Event Sequences With Recurrent Point Process Networks.
IEEE Trans. Neural Networks Learn. Syst., 2019

Modeling behaviors and lifestyle with online and social data for predicting and analyzing sleep and exercise quality.
Int. J. Data Sci. Anal., 2019

Improved Knowledge Distillation via Teacher Assistant: Bridging the Gap Between Student and Teacher.
CoRR, 2019

DyRep: Learning Representations over Dynamic Graphs.
Proceedings of the 7th International Conference on Learning Representations, 2019

Cross-View Policy Learning for Street Navigation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Point process modeling and optimization of social networks.
PhD thesis, 2018

Representation Learning over Dynamic Graphs.
CoRR, 2018

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution.
Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

More Robust Doubly Robust Off-policy Evaluation.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Conditional Generative Models for Temporal Point Processes.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Detecting Changes in Dynamic Events Over Networks.
IEEE Trans. Signal Inf. Process. over Networks, 2017

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Evolution.
J. Mach. Learn. Res., 2017

Hawkes Processes for Invasive Species Modeling and Management.
CoRR, 2017

Joint Modeling of Event Sequence and Time Series with Attentional Twin Recurrent Neural Networks.
CoRR, 2017

Wasserstein Learning of Deep Generative Point Process Models.
CoRR, 2017

Distilling Information Reliability and Source Trustworthiness from Digital Traces.
Proceedings of the 26th International Conference on World Wide Web, 2017

Wasserstein Learning of Deep Generative Point Process Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Fake News Mitigation via Point Process Based Intervention.
Proceedings of the 34th International Conference on Machine Learning, 2017

Correlated Cascades: Compete or Cooperate.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Detecting weak changes in dynamic events over networks.
CoRR, 2016

Multistage Campaigning in Social Networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Smart Broadcasting: Do You Want to be Seen?
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Learning Granger Causality for Hawkes Processes.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
On the network you keep: analyzing persons of interest using Cliqster.
Soc. Netw. Anal. Min., 2015

Correlated Cascades: Compete or Cooperate.
CoRR, 2015

A Continuous-time Mutually-Exciting Point Process Framework for Prioritizing Events in Social Media.
CoRR, 2015

Co-evolutionary Dynamics of Information Diffusion and Network Structure.
Proceedings of the 24th International Conference on World Wide Web Companion, 2015

Learning Latent Variable Models by Improving Spectral Solutions with Exterior Point Method.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

NetCodec: Community Detection from Individual Activities.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Back to the Past: Source Identification in Diffusion Networks from Partially Observed Cascades.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Shaping Social Activity by Incentivizing Users.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
From Local Similarity to Global Coding: An Application to Image Classification.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

Online Object Representation Learning and Its Application to Object Tracking.
Proceedings of the Lifelong Machine Learning, 2013

2011
Manifold Coarse Graining for Online Semi-supervised Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Efficient Iterative Semi-supervised Classification on Manifold.
Proceedings of the Data Mining Workshops (ICDMW), 2011


  Loading...