Lifting WALKSAT-Based Local Search Algorithms for MAP Inference. - Somdeb Sarkhel; Vibhav Gogate (StarAI@AAAI, 2013)

Lifted MAP Inference for Markov Logic Networks. - Somdeb Sarkhel; Deepak Venugopal; Parag Singla; Vibhav Gogate (AISTATS, 2014)

An Integer Polynomial Programming Based Framework for Lifted MAP Inference. - Somdeb Sarkhel; Deepak Venugopal; Parag Singla; Vibhav Gogate (NIPS, 2014)

Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs. - Deepak Venugopal; Somdeb Sarkhel; Vibhav Gogate (AAAI, 2015)

Fast Lifted MAP Inference via Partitioning. - Somdeb Sarkhel; Parag Singla; Vibhav Gogate (NIPS, 2015)

On Parameter Tying by Quantization. - Li Chou; Somdeb Sarkhel; Nicholas Ruozzi; Vibhav Gogate (AAAI, 2016)

Scaling-Up MAP and Marginal MAP Inference in Markov Logic. - Somdeb Sarkhel (AAAI, 2016)

Scalable Training of Markov Logic Networks Using Approximate Counting. - Somdeb Sarkhel; Deepak Venugopal; Tuan Anh Pham; Parag Singla; Vibhav Gogate (AAAI, 2016)

Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs. - Deepak Venugopal; Somdeb Sarkhel; Kyle Cherry (UAI, 2016)

Efficient Inference for Untied MLNs. - Somdeb Sarkhel; Deepak Venugopal; Nicholas Ruozzi; Vibhav Gogate (IJCAI, 2017)

User Segment Identification Based on Similarity in Content Consumption. - Somdeb Sarkhel; Wreetabrata Kar; Viswanathan Swaminathan 001 (ISM, 2017)

Personalized Video Recommendations for Shared Accounts. - Shuo Yang 004; Somdeb Sarkhel; Saayan Mitra; Viswanathan Swaminathan 001 (ISM, 2017)

Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks. - Li Chou; Pracheta Sahoo; Somdeb Sarkhel; Nicholas Ruozzi; Vibhav Gogate (AAAI, 2018)

Learning Mixtures of MLNs. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (AAAI, 2018)

Efficient Weight Learning in High-Dimensional Untied MLNs. - Khan Mohammad Al Farabi; Somdeb Sarkhel; Deepak Venugopal (AISTATS, 2018)

Scaling up Inference in MLNs with Spark. - Mohammad Maminur Islam; Khan Mohammad Al Farabi; Somdeb Sarkhel; Deepak Venugopal (IEEE BigData, 2018)

Content-Based Effectiveness Prediction of Video Advertisements. - Qi Lou; Somdeb Sarkhel; Saayan Mitra; Viswanathan Swaminathan 001 (ISM, 2018)

On Lifted Inference Using Neural Embeddings. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (AAAI, 2019)

Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models. - Craig Kelly; Somdeb Sarkhel; Deepak Venugopal (AISTATS, 2019)

Fine-Grained Explanations Using Markov Logic. - Khan Mohammad Al Farabi; Somdeb Sarkhel; Sanorita Dey; Deepak Venugopal (ECML/PKDD (2), 2019)

Scalable Bid Landscape Forecasting in Real-Time Bidding. - Aritra Ghosh 001; Saayan Mitra; Somdeb Sarkhel; Jason Xie; Gang Wu 013; Viswanathan Swaminathan 001 (ECML/PKDD (3), 2019)

Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (IEEE BigData, 2020)

Scaling Dnn-Based Video Analysis By Coarse-Grained And Fine-Grained Parallelism. - Phanwadee Sinthong; Kanak Mahadik; Somdeb Sarkhel; Saayan Mitra (ICME, 2020)

Optimal Bidding Strategy without Exploration in Real-time Bidding. - Aritra Ghosh 001; Saayan Mitra; Somdeb Sarkhel; Viswanathan Swaminathan 001 (SDM, 2020)

Inferring Individual Level Causal Models from Graph-based Relational Time Series. - Ryan A. Rossi; Somdeb Sarkhel; Nesreen K. Ahmed (CoRR, 2020)

Interpretable Explanations for Probabilistic Inference in Markov Logic. - Khan Mohammad Al Farabi; Somdeb Sarkhel; Sanorita Dey; Deepak Venugopal (IEEE BigData, 2021)

Contrastive Learning in Neural Tensor Networks using Asymmetric Examples. - Mohammad Maminur Islam; Somdeb Sarkhel; Deepak Venugopal (IEEE BigData, 2021)

Open-Domain Trending Hashtag Recommendation for Videos. - Swapneel Mehta; Somdeb Sarkhel; Xiang Chen; Saayan Mitra; Viswanathan Swaminathan 001; Ryan A. Rossi; Ali Aminian; Han Guo; Kshitiz Garg (ISM, 2021)

BOhance: Bayesian Optimization for Content Enhancement. - Trisha Mittal; Vishy Swaminathan; Somdeb Sarkhel; Ritwik Sinha; David Arbour; Saayan Mitra; Dinesh Manocha (ISM, 2021)

Evaluating Captioning Models using Markov Logic Networks. - Monika Shah; Somdeb Sarkhel; Deepak Venugopal (IEEE Big Data, 2022)

Contextualized Styling of Images for Web Interfaces using Reinforcement Learning. - Pooja Guhan; Saayan Mitra; Somdeb Sarkhel; Stefano Petrangeli; Ritwik Sinha; Viswanathan Swaminathan 001; Aniket Bera; Dinesh Manocha (ISM, 2022)

Question Modifiers in Visual Question Answering. - William Britton; Somdeb Sarkhel; Deepak Venugopal (LREC, 2022)

Towards Preserving Server-Side Privacy of On-Device Models. - Akanksha Atrey; Ritwik Sinha; Somdeb Sarkhel; Saayan Mitra; David Arbour; Akash Maharaj; Prashant J. Shenoy (WWW (Companion Volume), 2022)

A Faster k-means++ Algorithm. - Jiehao Liang; Somdeb Sarkhel; Zhao Song 002; Chenbo Yin 002; Danyang Zhuo (CoRR, 2022)

Verifying Relational Explanations: A Probabilistic Approach. - Abisha Thapa Magar; Anup Shakya; Somdeb Sarkhel; Deepak Venugopal (IEEE Big Data, 2023)

Efficient Estimation of Local Causal Effects in Graphs via Neighborhood Pooling. - Ryan A. Rossi; Somdeb Sarkhel; Nesreen K. Ahmed (IEEE Big Data, 2023)

On the Verification of Embeddings with Hybrid Markov Logic. - Anup Shakya; Abisha Thapa Magar; Somdeb Sarkhel; Deepak Venugopal (ICDM, 2023)

Flash: Concept Drift Adaptation in Federated Learning. - Kunjal Panchal; Sunav Choudhary; Subrata Mitra; Koyel Mukherjee; Somdeb Sarkhel; Saayan Mitra; Hui Guan 001 (ICML, 2023)

On the verification of Embeddings using Hybrid Markov Logic. - Anup Shakya; Abisha Thapa Magar; Somdeb Sarkhel; Deepak Venugopal (CoRR, 2023)

TAME-RD: Text Assisted Replication of Image Multi-Adjustments for Reverse Designing. - Pooja Guhan; Uttaran Bhattacharya; Somdeb Sarkhel; Vahid Azizi 005; Xiang Chen; Saayan Mitra; Aniket Bera; Dinesh Manocha (ACL (Findings), 2024)

Disentangling Fine-Tuning from Pre-Training in Visual Captioning with Hybrid Markov Logic. - Monika Shah; Somdeb Sarkhel; Deepak Venugopal (IEEE Big Data, 2024)

ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search. - Yuchen Zhuang; Xiang Chen; Tong Yu 001; Saayan Mitra; Victor S. Bursztyn; Ryan A. Rossi; Somdeb Sarkhel; Chao Zhang 014 (ICLR, 2024)

X-Reflect: Cross-Reflection Prompting for Multimodal Recommendation. - Hanjia Lyu; Ryan A. Rossi; Xiang Chen; Md. Mehrab Tanjim; Stefano Petrangeli; Somdeb Sarkhel; Jiebo Luo 001 (CoRR, 2024)

VISIAR: Empower MLLM for Visual Story Ideation. - Zhaoyang Xia; Somdeb Sarkhel; Md. Mehrab Tanjim; Stefano Petrangeli; Ishita Dasgupta 002; Yuxiao Chen 002; Jinxuan Xu; Di Liu 003; Saayan Mitra; Dimitris N. Metaxas (ACL (Findings), 2025)

Reparameterizing Hybrid Markov Logic Networks to handle Covariate-Shift in Representations. - Anup Shakya; Abisha Thapa Magar; Somdeb Sarkhel; Deepak Venugopal (UAI, 2025)

SKALD: Learning-Based Shot Assembly for Coherent Multi-Shot Video Creation. - Chen-Yi Lu; Md. Mehrab Tanjim; Ishita Dasgupta 002; Somdeb Sarkhel; Gang Wu 013; Saayan Mitra; Somali Chaterji (CoRR, 2025)

A Penalty Goes a Long Way: Measuring Lexical Diversity in Synthetic Texts Under Prompt-Influenced Length Variations. - Vijeta Deshpande; Ishita Dasgupta 002; Uttaran Bhattacharya; Somdeb Sarkhel; Saayan Mitra; Anna Rumshisky (CoRR, 2025)

On Explaining Visual Captioning with Hybrid Markov Logic Networks. - Monika Shah; Somdeb Sarkhel; Deepak Venugopal (CoRR, 2025)

Analyzing the Sensitivity of Vision Language Models in Visual Question Answering. - Monika Shah; Sudarshan Balaji; Somdeb Sarkhel; Sanorita Dey; Deepak Venugopal (CoRR, 2025)