David S. Rosenberg

Publication Activity (10 Years)

Years Active: 2007-2023
Publications (10 Years): 13

Top Topics

Multiattribute Utility

Language Modelling

Top Venues

Publications

Shiyue Zhang, Shijie Wu, Ozan Irsoy, Steven Lu, Mohit Bansal, Mark Dredze, David S. Rosenberg
MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies. ACL (1) (2023)
Shiyue Zhang, Shijie Wu, Ozan Irsoy, Steven Lu, Mohit Bansal, Mark Dredze, David S. Rosenberg
MixCE: Training Autoregressive Language Models by Mixing Forward and Reverse Cross-Entropies. CoRR (2023)
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David S. Rosenberg, Gideon Mann
BloombergGPT: A Large Language Model for Finance. CoRR (2023)
Ramakanth Pasunuru, David S. Rosenberg, Gideon Mann, Mohit Bansal
Dual Reinforcement-Based Specification Generation for Image De-Rendering. CoRR (2021)
Ramakanth Pasunuru, David S. Rosenberg, Gideon Mann, Mohit Bansal
Dual Reinforcement-Based Specification Generation for Image De-Rendering. SDU@AAAI (2021)
Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, Amanda Stent
Visual Attention Model for Cross-Sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning. FLAIRS Conference (2019)
Yuntian Deng, David S. Rosenberg, Gideon Mann
Challenges in End-to-End Neural Scientific Table Recognition. ICDAR (2019)
Siddharth Karamcheti, Gideon Mann, David S. Rosenberg
Adaptive Grey-Box Fuzz-Testing with Thompson Sampling. AISec@CCS (2018)
Siddharth Karamcheti, Gideon Mann, David S. Rosenberg
Improving Grey-Box Fuzzing by Modeling Program Behavior. CoRR (2018)
Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, Amanda Stent
Visual Attention Model for Cross-sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning. CoRR (2018)
Siddharth Karamcheti, Gideon Mann, David S. Rosenberg
Adaptive Grey-Box Fuzz-Testing with Thompson Sampling. CoRR (2018)
Mathieu Cliche, David S. Rosenberg, Dhruv Madeka, Connie Yee
Scatteract: Automated extraction of data from scatter plots. CoRR (2017)
Mathieu Cliche, David S. Rosenberg, Dhruv Madeka, Connie Yee
Scatteract: Automated Extraction of Data from Scatter Plots. ECML/PKDD (1) (2017)
Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
Collaborative Place Models. IJCAI (2015)
Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
Collaborative Ranking for Local Preferences. AISTATS (2014)
David S. Rosenberg, Dan Klein, Ben Taskar
Mixture-of-Parents Maximum Entropy Markov Models CoRR (2012)
David S. Rosenberg, Vikas Sindhwani, Peter L. Bartlett, Partha Niyogi
Multiview point cloud kernels for semisupervised learning [Lecture Notes]. IEEE Signal Process. Mag. 26 (5) (2009)
Vikas Sindhwani, David S. Rosenberg
An RKHS for multi-view learning and manifold co-regularization. ICML (2008)
David S. Rosenberg, Peter L. Bartlett
The Rademacher Complexity of Co-Regularized Kernel Classes. AISTATS (2007)
David S. Rosenberg, Dan Klein, Ben Taskar
Mixture-of-Parents Maximum Entropy Markov Models. UAI (2007)