Somdeb Sarkhel

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 40

Top Topics

Parameter Learning

Top Venues

Publications

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)
Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search. ICLR (2024)
Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal
Verifying Relational Explanations: A Probabilistic Approach. CoRR (2024)
Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
On the Verification of Embeddings with Hybrid Markov Logic. ICDM (2023)
Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search. CoRR (2023)
Anup Shakya, Abisha Thapa Magar, Somdeb Sarkhel, Deepak Venugopal
On the verification of Embeddings using Hybrid Markov Logic. CoRR (2023)
Ryan A. Rossi, Somdeb Sarkhel, Nesreen K. Ahmed
Efficient Estimation of Local Causal Effects in Graphs via Neighborhood Pooling. BigData (2023)
Abisha Thapa Magar, Anup Shakya, Somdeb Sarkhel, Deepak Venugopal
Verifying Relational Explanations: A Probabilistic Approach. BigData (2023)
Kunjal Panchal, Sunav Choudhary, Subrata Mitra, Koyel Mukherjee, Somdeb Sarkhel, Saayan Mitra, Hui Guan
Flash: Concept Drift Adaptation in Federated Learning. ICML (2023)
William Britton, Somdeb Sarkhel, Deepak Venugopal
Question Modifiers in Visual Question Answering. LREC (2022)
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)
Monika Shah, Somdeb Sarkhel, Deepak Venugopal
Evaluating Captioning Models using Markov Logic Networks. Big Data (2022)
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)
Jiehao Liang, Somdeb Sarkhel, Zhao Song, Chenbo Yin, Danyang Zhuo
A Faster k-means++ Algorithm. CoRR (2022)
Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal
Interpretable Explanations for Probabilistic Inference in Markov Logic. IEEE BigData (2021)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
Contrastive Learning in Neural Tensor Networks using Asymmetric Examples. IEEE BigData (2021)
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)
Trisha Mittal, Vishy Swaminathan, Somdeb Sarkhel, Ritwik Sinha, David Arbour, Saayan Mitra, Dinesh Manocha
BOhance: Bayesian Optimization for Content Enhancement. ISM (2021)
Ryan A. Rossi, Somdeb Sarkhel, Nesreen K. Ahmed
Inferring Individual Level Causal Models from Graph-based Relational Time Series. CoRR (2020)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks. IEEE BigData (2020)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Viswanathan Swaminathan
Optimal Bidding Strategy without Exploration in Real-time Bidding. SDM (2020)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Viswanathan Swaminathan
Optimal Bidding Strategy without Exploration in Real-time Bidding. CoRR (2020)
Phanwadee Sinthong, Kanak Mahadik, Somdeb Sarkhel, Saayan Mitra
Scaling Dnn-Based Video Analysis By Coarse-Grained And Fine-Grained Parallelism. ICME (2020)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan
Scalable Bid Landscape Forecasting in Real-time Bidding. CoRR (2020)
Craig Kelly, Somdeb Sarkhel, Deepak Venugopal
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models. AISTATS (2019)
Khan Mohammad Al Farabi, Somdeb Sarkhel, Sanorita Dey, Deepak Venugopal
Fine-Grained Explanations Using Markov Logic. ECML/PKDD (2) (2019)
Aritra Ghosh, Saayan Mitra, Somdeb Sarkhel, Jason Xie, Gang Wu, Viswanathan Swaminathan
Scalable Bid Landscape Forecasting in Real-Time Bidding. ECML/PKDD (3) (2019)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
On Lifted Inference Using Neural Embeddings. AAAI (2019)
Mohammad Maminur Islam, Somdeb Sarkhel, Deepak Venugopal
Learning Mixtures of MLNs. AAAI (2018)
Qi Lou, Somdeb Sarkhel, Saayan Mitra, Viswanathan Swaminathan
Content-Based Effectiveness Prediction of Video Advertisements. ISM (2018)
Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal
Efficient Weight Learning in High-Dimensional Untied MLNs. AISTATS (2018)
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)
Mohammad Maminur Islam, Khan Mohammad Al Farabi, Somdeb Sarkhel, Deepak Venugopal
Scaling up Inference in MLNs with Spark. IEEE BigData (2018)
Shuo Yang, Somdeb Sarkhel, Saayan Mitra, Viswanathan Swaminathan
Personalized Video Recommendations for Shared Accounts. ISM (2017)
Somdeb Sarkhel, Wreetabrata Kar, Viswanathan Swaminathan
User Segment Identification Based on Similarity in Content Consumption. ISM (2017)
Somdeb Sarkhel, Deepak Venugopal, Nicholas Ruozzi, Vibhav Gogate
Efficient Inference for Untied MLNs. IJCAI (2017)
Li Chou, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate
On Parameter Tying by Quantization. AAAI (2016)
Somdeb Sarkhel
Scaling-Up MAP and Marginal MAP Inference in Markov Logic. AAAI (2016)
Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla, Vibhav Gogate
Scalable Training of Markov Logic Networks Using Approximate Counting. AAAI (2016)
Deepak Venugopal, Somdeb Sarkhel, Kyle Cherry
Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. UAI (2016)
Deepak Venugopal, Somdeb Sarkhel, Vibhav Gogate
Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs. AAAI (2015)
Somdeb Sarkhel, Parag Singla, Vibhav Gogate
Fast Lifted MAP Inference via Partitioning. NIPS (2015)
Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate
An Integer Polynomial Programming Based Framework for Lifted MAP Inference. NIPS (2014)
Somdeb Sarkhel, Deepak Venugopal, Parag Singla, Vibhav Gogate
Lifted MAP Inference for Markov Logic Networks. AISTATS (2014)
Somdeb Sarkhel, Vibhav Gogate
Lifting WALKSAT-Based Local Search Algorithms for MAP Inference. AAAI Workshop: Statistical Relational Artificial Intelligence (2013)