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ORCIDSomdeb Sarkhel
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2020 – today
- 2024
[c38]Pooja Guhan, Uttaran Bhattacharya, Somdeb Sarkhel, Vahid Azizi, Xiang Chen, Saayan Mitra, Aniket Bera, Dinesh Manocha:
TAME-RD: Text Assisted Replication of Image Multi-Adjustments for Reverse Designing. ACL (Findings) 2024: 10710-10727- [c37]Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor S. Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang:
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search. ICLR 2024 - [i8]Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal:
Verifying Relational Explanations: A Probabilistic Approach. CoRR abs/2401.02703 (2024) - [i7]Hanjia Lyu, Ryan A. Rossi, Xiang Chen, Md. Mehrab Tanjim, Stefano Petrangeli, Somdeb Sarkhel, Jiebo Luo:
X-Reflect: Cross-Reflection Prompting for Multimodal Recommendation. CoRR abs/2408.15172 (2024) - 2023
- [c36]Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal:
Verifying Relational Explanations: A Probabilistic Approach. IEEE Big Data 2023: 108-115 - [c35]Ryan A. Rossi, Somdeb Sarkhel, Nesreen K. Ahmed:
Efficient Estimation of Local Causal Effects in Graphs via Neighborhood Pooling. IEEE Big Data 2023: 542-547 - [c34]Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal:
On the Verification of Embeddings with Hybrid Markov Logic. ICDM 2023: 1301-1306 - [c33]Kunjal Panchal, Sunav Choudhary, Subrata Mitra, Koyel Mukherjee, Somdeb Sarkhel, Saayan Mitra, Hui Guan:
Flash: Concept Drift Adaptation in Federated Learning. ICML 2023: 26931-26962 - [i6]Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor S. Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang:
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search. CoRR abs/2310.13227 (2023) - [i5]Anup Shakya
, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal:
On the verification of Embeddings using Hybrid Markov Logic. CoRR abs/2312.08287 (2023) - 2022
- [c32]Monika Shah, Somdeb Sarkhel, Deepak Venugopal:
Evaluating Captioning Models using Markov Logic Networks. IEEE Big Data 2022: 127-134 - [c31]Pooja Guhan, Saayan Mitra, Somdeb Sarkhel, Stefano Petrangeli, Ritwik Sinha, Viswanathan Swaminathan, Aniket Bera, Dinesh Manocha:
Contextualized Styling of Images for Web Interfaces using Reinforcement Learning. ISM 2022: 169-172 - [c30]William Britton, Somdeb Sarkhel, Deepak Venugopal:
Question Modifiers in Visual Question Answering. LREC 2022: 1472-1479 - [c29]Akanksha Atrey, Ritwik Sinha, Somdeb Sarkhel, Saayan Mitra, David Arbour, Akash Maharaj, Prashant J. Shenoy:
Towards Preserving Server-Side Privacy of On-Device Models. WWW (Companion Volume) 2022: 282-285 - [i4]Jiehao Liang, Somdeb Sarkhel, Zhao Song, Chenbo Yin, Danyang Zhuo:
A Faster k-means++ Algorithm. CoRR abs/2211.15118 (2022) - 2021
- [c28]Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal:
Contrastive Learning in Neural Tensor Networks using Asymmetric Examples. IEEE BigData 2021: 28-39 - [c27]Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal:
Interpretable Explanations for Probabilistic Inference in Markov Logic. IEEE BigData 2021: 1256-1264 - [c26]Trisha Mittal, Vishy Swaminathan, Somdeb Sarkhel, Ritwik Sinha, David Arbour, Saayan Mitra, Dinesh Manocha:
BOhance: Bayesian Optimization for Content Enhancement. ISM 2021: 17-24 - [c25]Swapneel Mehta, Somdeb Sarkhel, Xiang Chen, Saayan Mitra, Viswanathan Swaminathan, Ryan A. Rossi, Ali Aminian, Han Guo, Kshitiz Garg:
Open-Domain Trending Hashtag Recommendation for Videos. ISM 2021: 174-181 - 2020
- [c24]Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal:
Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks. IEEE BigData 2020: 54-63 - [c23]Phanwadee Sinthong, Kanak Mahadik, Somdeb Sarkhel, Saayan Mitra:
Scaling Dnn-Based Video Analysis By Coarse-Grained And Fine-Grained Parallelism. ICME 2020: 1-6 - [c22]Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Viswanathan Swaminathan:
Optimal Bidding Strategy without Exploration in Real-time Bidding. SDM 2020: 298-306 - [i3]Ryan A. Rossi, Somdeb Sarkhel, Nesreen K. Ahmed:
Inferring Individual Level Causal Models from Graph-based Relational Time Series. CoRR abs/2001.05993 (2020) - [i2]Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan:
Scalable Bid Landscape Forecasting in Real-time Bidding. CoRR abs/2001.06587 (2020) - [i1]Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Viswanathan Swaminathan:
Optimal Bidding Strategy without Exploration in Real-time Bidding. CoRR abs/2004.00100 (2020)
2010 – 2019
- 2019
- [c21]Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal:
On Lifted Inference Using Neural Embeddings. AAAI 2019: 7916-7923 - [c20]Craig Kelly, Somdeb Sarkhel, Deepak Venugopal:
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models. AISTATS 2019: 2907-2915 - [c19]Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan:
Scalable Bid Landscape Forecasting in Real-Time Bidding. ECML/PKDD (3) 2019: 451-466 - [c18]Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal:
Fine-Grained Explanations Using Markov Logic. ECML/PKDD (2) 2019: 614-629 - 2018
- [c17]Li Chou, Pracheta Sahoo, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate:
Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks. AAAI 2018: 2860-2867 - [c16]Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal:
Learning Mixtures of MLNs. AAAI 2018: 6359-6366 - [c15]Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal:
Efficient Weight Learning in High-Dimensional Untied MLNs. AISTATS 2018: 1637-1645 - [c14]Mohammad Maminur Islam, Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal:
Scaling up Inference in MLNs with Spark. IEEE BigData 2018: 118-125 - [c13]Qi Lou, Somdeb Sarkhel, Saayan Mitra, Viswanathan Swaminathan:
Content-Based Effectiveness Prediction of Video Advertisements. ISM 2018: 69-72 - 2017
- [c12]Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate:
Efficient Inference for Untied MLNs. IJCAI 2017: 4617-4624 - [c11]Shuo Yang, Somdeb Sarkhel, Saayan Mitra, Viswanathan Swaminathan:
Personalized Video Recommendations for Shared Accounts. ISM 2017: 256-259 - [c10]Somdeb Sarkhel, Wreetabrata Kar, Viswanathan Swaminathan:
User Segment Identification Based on Similarity in Content Consumption. ISM 2017: 300-303 - 2016
- [c9]Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla, Vibhav Gogate:
Scalable Training of Markov Logic Networks Using Approximate Counting. AAAI 2016: 1067-1073 - [c8]Li Chou, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate:
On Parameter Tying by Quantization. AAAI 2016: 3241-3247 - [c7]Somdeb Sarkhel:
Scaling-Up MAP and Marginal MAP Inference in Markov Logic. AAAI 2016: 4343- - [c6]Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry:
Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. UAI 2016 - 2015
- [c5]Deepak Venugopal, Somdeb Sarkhel, Vibhav Gogate:
Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs. AAAI 2015: 3606-3612 - [c4]Somdeb Sarkhel, Parag Singla, Vibhav Gogate:
Fast Lifted MAP Inference via Partitioning. NIPS 2015: 3240-3248 - 2014
- [c3]Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate:
Lifted MAP Inference for Markov Logic Networks. AISTATS 2014: 859-867 - [c2]Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate:
An Integer Polynomial Programming Based Framework for Lifted MAP Inference. NIPS 2014: 3302-3310 - 2013
- [c1]Somdeb Sarkhel, Vibhav Gogate:
Lifting WALKSAT-Based Local Search Algorithms for MAP Inference. StarAI@AAAI 2013
Coauthor Index
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last updated on 2024-10-16 20:30 CEST by the dblp team
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