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2020 – today
- 2024
[c12]Mark Dredze, Genta Indra Winata, Prabhanjan Kambadur, Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, David S. Rosenberg, Sebastian Gehrmann:
Academics Can Contribute to Domain-Specialized Language Models. EMNLP 2024: 5100-5110- 2023
- [c11]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: 9027-9050 - [i8]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 abs/2303.17564 (2023) - [i7]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 abs/2305.16958 (2023) - 2021
- [c10]Ramakanth Pasunuru, David S. Rosenberg, Gideon Mann, Mohit Bansal:
Dual Reinforcement-Based Specification Generation for Image De-Rendering. SDU@AAAI 2021 - [i6]Ramakanth Pasunuru, David S. Rosenberg, Gideon Mann, Mohit Bansal:
Dual Reinforcement-Based Specification Generation for Image De-Rendering. CoRR abs/2103.01867 (2021)
2010 – 2019
- 2019
- [c9]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 2019: 98-103 - [c8]Yuntian Deng, David S. Rosenberg, Gideon Mann:
Challenges in End-to-End Neural Scientific Table Recognition. ICDAR 2019: 894-901 - 2018
- [c7]Siddharth Karamcheti, Gideon Mann, David S. Rosenberg:
Adaptive Grey-Box Fuzz-Testing with Thompson Sampling. AISec@CCS 2018: 37-47 - [i5]Siddharth Karamcheti, Gideon Mann, David S. Rosenberg:
Adaptive Grey-Box Fuzz-Testing with Thompson Sampling. CoRR abs/1808.08256 (2018) - [i4]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 abs/1809.03684 (2018) - [i3]Siddharth Karamcheti, Gideon Mann, David S. Rosenberg:
Improving Grey-Box Fuzzing by Modeling Program Behavior. CoRR abs/1811.08973 (2018) - 2017
- [c6]Mathieu Cliche, David S. Rosenberg, Dhruv Madeka, Connie Yee:
Scatteract: Automated Extraction of Data from Scatter Plots. ECML/PKDD (1) 2017: 135-150 - [i2]Mathieu Cliche, David S. Rosenberg, Dhruv Madeka, Connie Yee:
Scatteract: Automated extraction of data from scatter plots. CoRR abs/1704.06687 (2017) - 2015
- [c5]Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara:
Collaborative Place Models. IJCAI 2015: 3612-3618 - 2014
- [c4]Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara:
Collaborative Ranking for Local Preferences. AISTATS 2014: 466-474 - 2012
- [i1]David S. Rosenberg, Dan Klein, Ben Taskar:
Mixture-of-Parents Maximum Entropy Markov Models. CoRR abs/1206.5261 (2012)
2000 – 2009
- 2009
- [j1]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): 145-150 (2009) - 2008
- [c3]Vikas Sindhwani, David S. Rosenberg:
An RKHS for multi-view learning and manifold co-regularization. ICML 2008: 976-983 - 2007
- [c2]David S. Rosenberg, Dan Klein, Ben Taskar:
Mixture-of-Parents Maximum Entropy Markov Models. UAI 2007: 318-325 - [c1]David S. Rosenberg, Peter L. Bartlett:
The Rademacher Complexity of Co-Regularized Kernel Classes. AISTATS 2007: 396-403
Coauthor Index
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