Somdeb Sarkhel

According to our database1, Somdeb Sarkhel authored at least 40 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
On the verification of Embeddings using Hybrid Markov Logic.
CoRR, 2023

ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search.
CoRR, 2023

Flash: Concept Drift Adaptation in Federated Learning.
Proceedings of the International Conference on Machine Learning, 2023

On the Verification of Embeddings with Hybrid Markov Logic.
Proceedings of the IEEE International Conference on Data Mining, 2023

Efficient Estimation of Local Causal Effects in Graphs via Neighborhood Pooling.
Proceedings of the IEEE International Conference on Big Data, 2023

Verifying Relational Explanations: A Probabilistic Approach.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
A Faster k-means++ Algorithm.
CoRR, 2022

Towards Preserving Server-Side Privacy of On-Device Models.
Proceedings of the Companion of The Web Conference 2022, Virtual Event / Lyon, France, April 25, 2022

Question Modifiers in Visual Question Answering.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

Contextualized Styling of Images for Web Interfaces using Reinforcement Learning.
Proceedings of the IEEE International Symposium on Multimedia, 2022

Evaluating Captioning Models using Markov Logic Networks.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
BOhance: Bayesian Optimization for Content Enhancement.
Proceedings of the IEEE International Symposium on Multimedia, 2021

Open-Domain Trending Hashtag Recommendation for Videos.
Proceedings of the IEEE International Symposium on Multimedia, 2021

Contrastive Learning in Neural Tensor Networks using Asymmetric Examples.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Interpretable Explanations for Probabilistic Inference in Markov Logic.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020
Inferring Individual Level Causal Models from Graph-based Relational Time Series.
CoRR, 2020

Optimal Bidding Strategy without Exploration in Real-time Bidding.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Scaling Dnn-Based Video Analysis By Coarse-Grained And Fine-Grained Parallelism.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2020

Augmenting Deep Learning with Relational Knowledge from Markov Logic Networks.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Scalable Bid Landscape Forecasting in Real-Time Bidding.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Fine-Grained Explanations Using Markov Logic.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

On Lifted Inference Using Neural Embeddings.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Content-Based Effectiveness Prediction of Video Advertisements.
Proceedings of the 2018 IEEE International Symposium on Multimedia, 2018

Scaling up Inference in MLNs with Spark.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

Efficient Weight Learning in High-Dimensional Untied MLNs.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Learning Mixtures of MLNs.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Personalized Video Recommendations for Shared Accounts.
Proceedings of the 19th IEEE International Symposium on Multimedia, 2017

User Segment Identification Based on Similarity in Content Consumption.
Proceedings of the 19th IEEE International Symposium on Multimedia, 2017

Efficient Inference for Untied MLNs.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
Non-parametric Domain Approximation for Scalable Gibbs Sampling in MLNs.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Scalable Training of Markov Logic Networks Using Approximate Counting.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

Scaling-Up MAP and Marginal MAP Inference in Markov Logic.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

On Parameter Tying by Quantization.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Fast Lifted MAP Inference via Partitioning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Just Count the Satisfied Groundings: Scalable Local-Search and Sampling Based Inference in MLNs.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
An Integer Polynomial Programming Based Framework for Lifted MAP Inference.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Lifted MAP Inference for Markov Logic Networks.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Lifting WALKSAT-Based Local Search Algorithms for MAP Inference.
Proceedings of the Statistical Relational Artificial Intelligence, 2013


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