RESEARCH













Parag Singla

Professor
Department of Computer Science and Engineering
Indian Instiute of Technology
Hauz Khas, New Delhi. 110016

Phone : 91-11-26596064
Email : parags [at] cse [dot] iitd [dot] ac [dot] in


Home     Research     Teaching     Miscellaneous    


PhD Thesis

Markov Logic: Theory, Algorithms and Applications. Parag Singla. PhD Dissertation, University of Washington, Seattle, 2009.

Publications

Journal Papers

2022

SSDMM-VAE: variational multi-modal disentangled representation learning. Arnab Kumar Mondal, Ajay Sailopal, Parag Singla, AP Prathosh. Applied Intelligence, pages 1-15, 2022. Publisher: Springer.

2021

xViTCOS: Explainable Vision Transformer Based COVID-19 Screening Using Radiography Arnab Kumar Mondal, Arnab Bhattacharjee, Parag Singla, AP Prathosh. IEEE Journal of Translational Engineering in Health and Medicine, Vol 10, pages 1-10. Publisher: IEEE.

scRAE: Deterministic Regularized Autoencoders with Flexible Priors for Clustering Single-cell Gene Expression Data Arnab Kumar Mondal, Himanshu Asnani, Parag Singla and Prathosh AP. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021. Publisher: IEEE.

Constrained BERT BiLSTM CRF for Understanding Multi-Sentence Entity-Seeking Questions. Danish Contractor, Barun Patra, Mausam and Parag Singla. Natural Language Engineering, Vol 27 (1), pages 65-87, 2021. Publisher: Cambridge University Press. [pdf]. (online version published in Feb 2020.)

2017

Analysis and Characterization of Comparison Shopping Behavior in the Mobile Handset Domain. Mona Gupta, Happy Mittal, Parag Singla and Amitabha Bagchi. Electronic Commerce Research, Vol 17 (3), pages 521-551, 2017. Publisher: Springer. [pdf]

2016

Technical Perspective: Combining Logic and Probability. Henry Kautz and Parag Singla. Communications of the ACM, Vol. 59 (7), pages: 106, 2016. Publisher: ACM. [pdf]

Lazy Generic Cuts. Dinesh Khandelwal, Kush Bhatia, Chetan Arora and Parag Singla. Computer Vision and Image Understanding (CVIU) Special Issue on Inference and Learning of Graphical Models, Vol 143, pages 80-91, 2016. Publisher: Elsevier. [pdf]

2015

On the Role of Conductance, Geography and Topology in Predicting Hashtag Virality. Siddharth Bora, Harvineet Singh, Anirban Sen, Amitabha Bagchi and Parag Singla. Social Network Analysis and Mining, Vol 5(1), pages 1-15, 2015. Publisher: Springer.[pdf]

Conference Papers

2023

Learning Neuro-symbolic Programs for Language-Guided Robot Manipulation. Namasivayam K, Himanshu Singh, Vishal Bindal, Arvan Tuli, Vishwajeet Agrawal, Rahul Jain, Parag Singla and Rohan Paul. IEEE International Conference on Robotics and Automation (ICRA), 2023 (accepted). London, UK.

2022

A Solver-free Framework for Scalable Learning in Neural-ILP Architectures. Yatin Nandwani, Rishabh Ranjan, Mausam and Parag Singla. Thirty Sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. New Orleans, LA, USA (hybrid mode).

Neural Models for Output-Space Invariance in Combinatorial Problems. Yatin Nandwani, Vidit Jain, Mausam and Parag Singla. Tenth International Conference on Learning Representations (ICLR), 2022. Virtual, online.

SymNet 2.0: Effectively handling Non-Fluents and Actions in Generalized Neural Policies for RDDL Relational MDPs. Vishal Sharma, Daman Arora, Florian Geiber, Mausam and Parag Singla. Thrity Eighth International Conference on Uncertainty in Artificial Intelligence (UAI), 2022. Eindhoven, Netherlands (hybrid mode).

PARE: A Simple and Strong Baseline for Monolingual and Multilingual Distantly Supervised Relation Extraction. Vipul Rathore, Kartikeya Badola, Parag Singla and Mausam. Sixtieth International Conference of the Association for Computational Linguistics (ACL), 2022. Dublin, Ireland (hybrid mode).

2021

Answering POI-recommendation Questions using Tourism Reviews. Danish Contractor, Krunal Shah, Aditi Pratap, Parag Singla and Mausam. Thirtieth International Conference on Information and Knowledge Management (CIKM), 2021. Virtual online.

FlexAE: Flexibly Learning Latent Priors for Wasserstein Auto Encoders. Arnab Kumar Mondal, Himanshu Asnani, Parag Singla and Prathosh AP. Thirty Seventh International Conference on Uncertainty in Artificial Intelligence (UAI), 2021. Virtual online.

Explanations for CommonSenseQA: New Dataset and Models. Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla and Dinesh Garg. Fifty Ninth Internaional (Joint) Conference of the Association for Computational Linguistics (ACL), 2021. Virtual online.

Neural Learning of One-of-Many Solutions for Combinatorial Problems in Structured Output Spaces. Yatin Nandwani, Deepanshu Jindal, Mausam and Parag Singla. Ninth International Conference on Learning Representations (ICLR), 2021. Virtual online.

Joint Spatio-Textual Reasoning for Answering Tourism Questions. Danish Contractor, Shashank Goel, Mausam and Parag Singla. The Web Conference (WWW), 2021. Virtual online.

2020

MaskAAE: Latent Space Optimization for Adversarial Autoencoders. Arnab Kumar Mondal, Sankalan Pal Chowdhury, Aravind Jayendran, Parag Singla, Himanshu Asnani and Prathosh AP. Thirty Sixth International Conference on Uncertainty in Artificial Intelligence (UAI), 2020. Virtual online. Supplementary Material

OxKBC: Outcome Explanation for Factorization Based Knowledge Base Completion. Yatin Nandwani, Ankesh Gupta, Aman Agrawal, Mayank Singh Chauhan, Parag Singla and Mausam. Conference on Automated Knowledge Base Construction (AKBC), 2020. Virtual online.

2019

A Primal-Dual Formulation for Deep Learning with Constraints. Yatin Nandwani, Abhishek Pathak, Mausam and Parag Singla. Thirty Third International Conference on Neural Information Processing Systems (NeurIPS), 2019. Vancouver, Canada. Supplementary Material

Domain-Size Aware Markov Logic Networks. Happy Mittal, Ayush Bhardwaj, Vibhav Gogate and Parag Singla. Twenty Second International Conference on Artificial Intelligence and Statistics (AISTATS), 2019 (pp. 3216-3224). Naha, Okinawa, Japan. Supplementary Material

Price Forecasting and Anomaly Detection for Agricultural Commodities in India. Lovish Madaan, Ankur Sharma, Praneet Khandelwal, Shivank Goel, Parag Singla and Aaditeshwar Seth. Second Annual ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS), 2019 (pp. 52-64). Accara, Ghana. Supplementary Material

2018

Lifted Marginal MAP Inference. Vishal Sharma, Noman Ahmed Sheikh, Vibhav Gogate and Parag Singla. Thirty Fourth Conferene on Uncertainty in Artificial Intelligence (UAI), 2018. Monterey, CA, USA.

Block-Value Symmetries in Probabilistic Grpahical Models. Gagan Madan, Ankit Anand, Mausam and Parag Singla. Thirty Fourth Conferene on Uncertainty in Artificial Intelligence (UAI), 2018. Monterey, CA, USA.

Learning Higher Order Potentials for MRFs. Dinesh Khandelwal, Parag Singla and Chetan Arora. IEEE Winter Conference on Applications of Computer Vision (WACV), 2018 (812-820). Lake Tahoe, NV, USA.

2017

Coarse-to-fine Lifted MAP inference in Computer Vision. Haroun Habeeb and Ankit Anand, Mausam and Parag Singla. Twenty Sixth International Conference on Artificial Intelligence (IJCAI), 2017 (4595-4602). Melbourne, Australia.

Non-Count Symmetries in Boolean and Multi-Valued Probabilistic Graphical Models. Ankit Anand, Ritesh Noothigattu, Parag Singla and Mausam. Twentieth International Conference on Artificial Intelligence and Statistics (AISTATS), 2017 (1541-1549). Fort Lauderdale, Florida, USA.

2016

Contextual Symmetries in Probabilistic Graphical Models. Ankit Anand, Aditya Grover, Mausam and Parag Singla. Twenty Fifth International Conference on Artificial Intelligence (IJCAI), 2016 (3560-3568). New York, NY, USA.

Unsupervised Alignment of Actions in Video with Text Descriptions. Young Chol Song, Iftekar Naim, Abdullah Al Mamun, Kaustubh Kulkarni, Parag Singla, Jiebo Luo, Daniel Gildea and Henry Kautz. Twenty Fifth International Conference on Artificial Intelligence (IJCAI), 2016 (2025-2031). New York, NY, USA.

Entity Balanced Gaussian pLSA for Automated Comparison. Danish Contractor, Mausam and Parag Singla. Fifteenth Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2016 (5365-5374). San Diego, CA, USA.

Min Norm Point Algorithm for Higher Order MRF-MAP Inference.Ishant Shanu, Chetan Arora and Parag Singla. Twnety Ninth IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2016 (5365-5374). Las Vegas, Nevada, USA.

OGA-UCT: On-the-Go Abstractions in UCT. Ankit Anand, Ritesh Noothigattu, Mausam and Parag Singla. Twenty Sixth International Conference on Automated Planning and Scheduling (ICAPS), 2016 (29-37). London, United Kingdom.

Scalable Training of Markov Logic Networks Using Approximate Counting. Somdeb Sarkhel, Deepak Venugopal, Tuan Anh Pham, Parag Singla and Vibhav Gogate. Thirtieth AAAI Conference on Artificial Intelligence (AAAI), 2016 (1067-1073). Phoenix, Arizona, USA.

2015

Lifted Inference Rules with Constarints. Happy Mittal, Anuj Mahajan, Vibhav Gogate and Parag Singla. Twenty Ninth Annual Conference on Neural Information Processing Systems (NIPS), 2015. Montreal, Canada. Supplementary Material

Lifted Symmetry Detection and Breaking for MAP Inference. Timothy Kopp, Parag Singla and Henry Kautz. Twenty Ninth Annual Conference on Neural Information Processing Systems (NIPS), 2015. Montreal, Canada. Supplementary Material

Fast lifted MAP Inference via Partitioning. Somdeb Sarkhel, Parag Singla and Vibhav Gogate. Twenty Ninth Annual Conference on Neural Information Processing Systems (NIPS), 2015. Montreal, Canada.

ASAP-UCT: Abstraction of State Action Pairs in UCT. Ankit Anand, Aditya Grover, Mausam and Parag Singla. Twenty Fourth International Conference on Artificial Intelligence (IJCAI), 2015 (1509-1515). Buenos Aires, Argetina.

2014

New Rules for Domain Independent Lifted MAP Inference. Happy Mittal, Prasoon Goyal, Vibhav Gogate and Parag Singla. Twenty Eighth Annual Conference on Neural Information Processing Systems (NIPS), 2014 (649-657). Montreal, Canada. Supplementary Material

An Integer Polynomial Programming Based Framework for Lifted MAP Inference. Somdeb Sarkhel, Deepak Venugopal, Parag Singla and Vibhav Gogate. Twenty Eighth Annual Conference on Neural Information Processing Systems (NIPS), 2014 (3302-3310). Montreal, Canada.

Approximate Lifting Techniques for Belief Propagation. Parag Singla, Aniruddh Nath and Pedro Domingos. Twenty-eighth AAAI Conference on Artificial Intelligence, 2014 (2497-2504). Quebec City, Canada.

Lifted MAP Inference for Markov Logic Networks. Somdeb Sarkhel, Deepak Venugopal, Parag Singla and Vibhav Gogate. Seventeenth International Conference on Artificial Intelligence and Statistics, 2014 (859-867). Reykjavik, Iceland.

2013

Scaling-up Quadratic Programming Feature Selection (short paper). Yamuna Prasad, K.K. Biswas and Parag Singla. Late-Breaking Track at Twenty-Seventh Conference on Artificial Intelligence (AAAI), 2013. Bellevue, WA.

2011 (and earlier)

Constraint Propagation for Efficient Inference in Markov Logic. Tivadar Papai, Parag Singla and Henry Kautz. Seventeenth International Conference on Principles and Practice of Constraint Programming, 2011 (pp. 691 - 705). Perugia, Italy.

Abductive Markov Logic for Plan Recognition. Parag Singla and Raymond J. Mooney. Twenty-fifth National Conference on Artificial Intelligence, 2011 (1069 - 1075). San Fransisco, CA.

Lifted First-Order Belief Propagation. Parag Singla and Pedro Domingos. Twenty-third Conference on Artificial Intelligence, 2008 (pp. 1094-1099). Chicago, IL.

Yes, There is a Correlation - From Social Networks to Personal Behavior on the Web. Parag Singla and Matthew Richardson. Seventeenth International Conference on World Wide Web, 2008 (pp. 655-664). Beijing, China.

Markov Logic in Infinite Domains. Parag Singla and Pedro Domingos. Twenty Third Conference on Uncertainty in Artificial Intelligence, 2007 (pp. 368-375). Vancouver, Canada.

Entity Resolution with Markov Logic. Parag Singla and Pedro Domingos. Sixth International Conference on Data Mining (pp. 572-582), 2006. Hong Kong, China.

Memory-Efficient Inference in Relational Domains. Parag Singla and Pedro Domingos. Twenty-First Conference on Artificial Intelligence (pp. 488-493), 2006. Boston, MA.

Unifying Logical and Statistical AI. Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew Richardson and Parag Singla. Twenty-First Conference on Artificial Intelligence (pp. 2-7), 2006. Boston, MA.

Discriminative Training of Markov Logic Networks. Parag Singla and Pedro Domingos. Twentieth National Conference on Artificial Intelligence (pp. 868-873), 2005. Pittsburgh, PA.

Object Identification with Attribute-Mediated Dependences. Parag Singla and Pedro Domingos. Ninth European Conference on Principles and Practice of Knowledge Discovery in Databases (pp. 297-308), 2005. Porto, Portugal. Winner of the Best Paper award.

User Interaction in the BANKS System (demo paper) .  B. Aditya, Soumen Chakrabarti, Rushi Desai, Arvind Hulgeri, Hrishikesh Karambelkar, Rupesh Nasre, Parag and S. Sudarshan. International Conference on Data Engineering (pp. 786-788), 2003. Bangalore, India.

BANKS: Browsing and Keyword Searching in Relational Databases (demo paper). B. Aditya, Gaurav Bhalotia, Soumen Chakrabarti, Arvind Hulgeri, Charuta Nakhe, Parag and S. Sudarshan. International Conference on Very Lage Databases (pp. 1083-86), 2002. Hong Kong, China.

Book Chapters

2014

Plan Recognition using Statistical Relational Models. Sindhu Raghavan, Parag Singla and Raymond J. Mooney. In G. Sukthankar, C. Geib, H.H.Bui, D. Pynadath and R.P. Goldman(Eds.), Plan, Activity, and Intent Recognition: Theory and Practice, 2014. Burlington, Massachusetts: Morgan Kaufmann.

2011 (and earlier)

Markov Logic: A Language and Algorithms for Link Mining. Pedro Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, and Parag Singla. In P. Yu, C. Faloutsos, and J. Han (eds.), Link Mining: Models, Algorithms and Applications (pp. 135-162), 2010. New York: Springer.

Markov Logic. Pedro Domingos, Stanley Kok, Daniel Lowd, Hoifung Poon, Matthew Richardson, and Parag Singla. In L. De Raedt, P. Frasconi, K. Kersting and S. Muggleton (eds.), Probabilistic Inductive Logic Programming (pp. 92-117), 2008. New York: Springer.

Just Add Weights: Markov Logic for the Semantic Web. Pedro Domingos, Daniel Lowd, Stanley Kok, Hoifung Poon, Matthew Richardson, and Parag Singla. In P. C. G. Costa, C. d'Amato, N. Fanizzi, K. B. Laskey, K. J. Laskey, T. Lukasiewicz, M. Nickles, and M. Pool (eds.), Uncertain Reasoning for the Semantic Web (pp. 1-25), 2008. New York: Springer

Workshop Papers

2022

Image Manipulation via Neuro-Symbolic Networks. Harman Singh, Poorva Garg, Mohit Gupta, Kevin Shah, Arnab Kumar Mondal, Dinesh Khandelwal, Parag Singla and Dinesh Garg. NeurIPS Workshop on Neuro Causal and Symbolic AI, 2022. New Orleans, LA, USA (hybrid).

Learning Neuro-symbolic Programs for Language-Guided Robotic Manipulation. Namasivayam Kalithasan, Himanshu Singh, Vishal Bindal, Arnav Tuli, Vishwajeet Agrawal, Rahul Jain, Parag Singla and Rohan Paul. NeurIPS Workshop on Neuro Causal and Symbolic AI, 2022. New Orleans, LA, USA (hybrid).

Few Shot Generative Domain Adaptation Via Inference-Stage Latent Learning in GANs. . Arnab Kumar Mondal, Piyush Tiwary, Parag Singla, Prathosh AP. NeurIPS Workshop on Distribution Shifts: Connecting Methods and Applications, 2022. New Orleans, LA, USA (hybrid).

2021

Explanations for CommonsenseQA: New Dataset and Models. Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, Dinesh Khandelwal, Parag Singla, Dinesh Garg. AKBC Workshop on Commonsense Reasoning and Knowledge Bases, 2021. Virtual, online.

Learning Robot Manipulation Programs: A Neuro-Symbolic Approach. Vishwajeet Agrawal, Rahul Jain, Parag Singla and Rohan Paul. Robotics Science and Systems (RSS) Workshop on Declarative and Neurosymbolic Representations in Robotic Learning and Control, 2021. Virutal online.

Towards an Interpretable Latent Space in Structured Models for Video Prediction. Rushil Gupta, Vishal Sharma, Yash Jain, Yitao Liang, Guy Van den Broeck, Parag Singla. IJCAI Workshop on Weakly Supervised Representation Learning, 2021. Virtual Online.

2020

Advances in Symmetry Breaking for SAT Modulo Theories. Saket Dingliwal, Ronak Agarwal, Happy Mittal and Parag Singla. AAAI Workshop on Statistical Relational AI (StarAI), 2020, New York, NY, USA.

2019

Exploiting Test Time Evidence to Improve Predictions of Deep Neural Networks. Dinesh Khandelwal, Suyash Agrawal, Parag Singla and Chetan Arora. NeurIPS Workshop on Learning with Rich Experience (LIRE): Integration of Learning Paradigms, 2019. Vancouver, Canada.

Understanding Complex Multi-sentence Entity Seeking Questions. Danish Contractor, Barun Patra, Mausam, Parag Singla. AAAI-19 Workshop on Reasoning and Complex QA, 2019. Honolulu, Hawaii, USA.

2018

Lifted Inference for Faster Training (LIFT) in End-to-End nerual-CRF models. Yatin Nandwani, Ankit Anand, Mausam and Parag Singla. NeurIPS Workshop on Relational Representation Learning (R2L), 2018. Montreal, Quebec, Canada.

Block-Value Symmetries in Probabilistic Graphical Models. Gagan Madan, Ankit Anand, Mausam and Parag Singla. IJCAI/ICML Workshop on Statistical Relational AI (StaRAI), 2018. Stockholm, Sweden.

Lifted Marginal MAP Inference. Vishal Sharma, Noman Ahmed Sheikh, Happy Mittal, Vibhav Gogate and Parag Singla. IJCAI/ICML Workshop on Statistical Relational AI (StaRAI), 2018. Stockholm, Sweden.

Domain Aware Markov Logic Networks. Happy Mittal, Ayush Bhardwaj, Vibhav Gogate and Parag Singla. IJCAI/ICML Workshop on Statistical Relational AI (StaRAI), 2018. Stockholm, Sweden.

2017

Coarse-to-Fine Lifted MAP Inference in Computer Vision. Haroun Habeeb, Ankit Anand, Mausam and Parag Singla. UAI Workshop on Statistical Relational AI (StarAI), 2017. Sydney, Australia.

Non-Count Symmetries in Boolean and Multi-valued Probabilistic Graphical Models. Ankit Anand, Ritesh Noothigattu, Mausam and Parag Singla. UAI Workshop on Statistical Relational AI (StarAI), 2017. Sydney, Australia.

Conditional Term Equivalent Symmetry Breaking for SAT. Tim Kopp, Parag Singla and Henry Kautz. AAAI Workshop on Symbolic Inference and Optimization, 2017. San Francisco, CA, USA.

2016

Contextual Symmetries in Probabilistic Graphical Models. Ankit Anand, Aditya Grover, Mausam and Parag Singla. IJCAI Workshop on Statistical Relation AI (StaRAI), 2016. New York, NY, USA. Winner of the Best Paper Award

Fine Grained Weight Learning in Markov Logic Networks. Happy Mittal, Shubhankar Suman Singh, Vibhav Gogate and Parag Singla. IJCAI Workshop on Statistical Relation AI (StaRAI), 2016. New York, NY, USA.

Lifted Region-Based Belief Propagation. David Smith, Parag Singla and Vibhav Gogate. IJCAI Workshop on Statistical Relation AI (StaRAI), 2016. New York, NY, USA.

Towrads Caching Symmetrical Sub-theories for Weighted Model Counting Tim Kopp, Parag Singla and Henry Kautz. AAAI Workshop on Beyond NP, 2016. Phoenix, Arizona, USA.

2014

Characterizing Comparison Shopping Behavior: A Case Study . Mona Gupta, Happy Mittal, Parag Singla and Amitabha Bagchi. Workshop on Big Data Customer Analytics (BDCA), 2014. Co-located with ICDE-14. Chicago, IL, USA.

2013

Feature Selection using One Class SVM: A New Perspective . Yamuna Prasad, K.K. Biswas and Parag Singla . NIPS Workshop on Machine Learning in Computational Biology, 2013. Lake Tahoe, Nevada, USA.

2011 (and earlier)

Approximate Lifted Belief Propagation. Parag Singla, Aniruddh Nath and Pedro Domingos. AAAI Workshop on Statistical Relation AI (pp. 92-97), 2010. Atlanta, GA.

Discovery of Social Relationships in Consumer Photo Collections using Markov Logic. Parag Singla, Henry Kautz, Jiebo Luo and Andrew Gallagher. CVPR Workshop on Semantic Learning and Applications in Multimedia (pp. 1-7), 2008. Anchorage, Alaska.

Multi-Relational Record Linkage. Parag and Pedro Domingos. KDD Workshop on Multi-Relational Data Mining (pp. 31-48), 2004. Seattle, WA.

Patents

Using Joint Communication and Search Data. Matthew Richardson and Parag Singla. Microsoft Corporation, Issued Apr. 2012.

Discovering Social Relationships from Personal Photo Collections. Jiebo Luo, Parag Singla, Henry Kautz and Andrew Gallagher. Eastman Kodak Company, Issued May 2011.

Software

Alchemy: A system for statistical relational learning and inference, based on Markov logic representation.