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- Kuldeep S. Meel
University of Toronto, Canada
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Publication search results
found 188 matches
- 2024
- Kuldeep S. Meel
, Sourav Chakraborty
, Umang Mathur
:
A faster FPRAS for #NFA. Proc. ACM Manag. Data 2(2): 112 (2024) - Aduri Pavan
, Sourav Chakraborty
, N. V. Vinodchandran
, Kuldeep S. Meel
:
On the Feasibility of Forgetting in Data Streams. Proc. ACM Manag. Data 2(2): 102 (2024) - Mohimenul Kabir, Supratik Chakraborty, Kuldeep S. Meel:
Exact ASP Counting with Compact Encodings. AAAI 2024: 10571-10580 - Kuldeep S. Meel, Supratik Chakraborty, S. Akshay:
Auditable Algorithms for Approximate Model Counting. AAAI 2024: 10654-10661 - Arijit Shaw, Brendan Juba, Kuldeep S. Meel:
An Approximate Skolem Function Counter. AAAI 2024: 8108-8116 - Suwei Yang
, Kuldeep S. Meel:
Engineering an Exact Pseudo-Boolean Model Counter. AAAI 2024: 8200-8208 - Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, Kuldeep S. Meel:
Equivalence Testing: The Power of Bounded Adaptivity. AISTATS 2024: 3592-3600 - Antoine Amarilli, Timothy van Bremen, Kuldeep S. Meel:
Conjunctive Queries on Probabilistic Graphs: The Limits of Approximability. ICDT 2024: 15:1-15:20 - Arijit Shaw, Kuldeep S. Meel:
CSB: A Counting and Sampling Tool for Bit-vectors. SMT@CAV 2024: 36-43 - Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, Kuldeep S. Meel:
Equivalence Testing: The Power of Bounded Adaptivity. CoRR abs/2403.04230 (2024) - Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran:
Total Variation Distance for Product Distributions is #P-Complete. CoRR abs/2405.08255 (2024) - Yong Kiam Tan, Jiong Yang, Mate Soos, Magnus O. Myreen, Kuldeep S. Meel:
Formally Certified Approximate Model Counting. CoRR abs/2406.11414 (2024) - Kuldeep S. Meel, Alexis de Colnet:
An FPRAS for #nFBDD. CoRR abs/2406.16515 (2024) - Kuldeep S. Meel, Alexis de Colnet:
#CFG and #DNNF admit FPRAS. CoRR abs/2406.18224 (2024) - 2023
- A. Pavan, N. V. Vinodchandran, Arnab Bhattacharyya, Kuldeep S. Meel:
Model Counting Meets Distinct Elements. Commun. ACM 66(9): 95-102 (2023) - Dinesh Kumar Vishwakarma, Priyanka Meel, Ashima Yadav, Kuldeep Singh:
A framework of fake news detection on web platform using ConvNet. Soc. Netw. Anal. Min. 13(1): 24 (2023) - A. Pavan
, N. Variyam Vinodchandran
, Arnab Bhattacharyya
, Kuldeep S. Meel
:
Model Counting Meets F0 Estimation. ACM Trans. Database Syst. 48(3): 7:1-7:28 (2023) - Yong Lai, Kuldeep S. Meel, Roland H. C. Yap:
Fast Converging Anytime Model Counting. AAAI 2023: 4025-4034 - Aduri Pavan
, Kuldeep S. Meel, N. V. Vinodchandran
, Arnab Bhattacharyya:
Constraint Optimization over Semirings. AAAI 2023: 4070-4077 - Ansuman Banerjee, Shayak Chakraborty, Sourav Chakraborty, Kuldeep S. Meel, Uddalok Sarkar, Sayantan Sen
:
Testing of Horn Samplers. AISTATS 2023: 1301-1330 - Jiong Yang, Kuldeep S. Meel:
Rounding Meets Approximate Model Counting. CAV (2) 2023: 132-162 - Priyanka Golia, Subhajit Roy, Kuldeep S. Meel:
Synthesis with Explicit Dependencies. DATE 2023: 1-6 - Bishwamittra Ghosh
, Debabrota Basu
, Kuldeep S. Meel
:
"How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity Analysis. FAccT 2023: 138-148 - Kuldeep S. Meel:
Distribution Testing: The New Frontier for Formal Methods. FMCAD 2023: 2 - Diptarka Chakraborty, Sourav Chakraborty, Gunjan Kumar, Kuldeep S. Meel:
Approximate Model Counting: Is SAT Oracle More Powerful Than NP Oracle? ICALP 2023: 123:1-123:17 - Arnab Bhattacharyya, Sutanu Gayen, Kuldeep S. Meel, Dimitrios Myrisiotis, A. Pavan, N. V. Vinodchandran
:
On Approximating Total Variation Distance. IJCAI 2023: 3479-3487 - Anna L. D. Latour, Arunabha Sen, Kuldeep S. Meel:
Solving the Identifying Code Set Problem with Grouped Independent Support. IJCAI 2023: 1971-1978 - Mate Soos, Divesh Aggarwal, Sourav Chakraborty, Kuldeep S. Meel, Maciej Obremski:
Engineering an Efficient Approximate DNF-Counter. IJCAI 2023: 2031-2038 - Suwei Yang, Victor C. Liang, Kuldeep S. Meel:
Scalable Probabilistic Routes. ENIGMA@KR 2023: 64-74 - Mohimenul Kabir, Kuldeep S. Meel:
A Fast and Accurate ASP Counting Based Network Reliability Estimator. LPAR 2023: 270-287
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