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Publication search results
found 74 matches
- 2023
- Jai Moondra, Aditya Sahdev, Amitabha Tripathi:
Exact and approximate results on the least size of a graph with a given degree set. Discret. Appl. Math. 333: 32-42 (2023) - Yao Tian, Tingyun Yan, Ruiyuan Zhang, Kai Huang, Bolong Zheng, Xiaofang Zhou:
A Learned Cuckoo Filter for Approximate Membership Queries over Variable-sized Sliding Windows on Data Streams. Proc. ACM Manag. Data 1(4): 264:1-264:26 (2023) - Rong Gu, Han Li, Haipeng Dai, Wenjie Huang, Jie Xue, Meng Li, Jiaqi Zheng, Haoran Cai, Yihua Huang, Guihai Chen:
ShadowAQP: Efficient Approximate Group-by and Join Query via Attribute-oriented Sample Size Allocation and Data Generation. Proc. VLDB Endow. 16(13): 4216-4229 (2023) - Ewan Davies, Will Perkins:
Approximately Counting Independent Sets of a Given Size in Bounded-Degree Graphs. SIAM J. Comput. 52(2): 618-640 (2023) - Sayan Bhattacharya, Peter Kiss, Thatchaphol Saranurak:
Dynamic (1+ϵ)-Approximate Matching Size in Truly Sublinear Update Time. FOCS 2023: 1563-1588 - Sayan Bhattacharya, Peter Kiss, Thatchaphol Saranurak:
Dynamic $(1+ε)$-Approximate Matching Size in Truly Sublinear Update Time. CoRR abs/2302.05030 (2023) - 2022
- Xuebin Su, Hongzhi Wang:
MISS: finding optimal sample sizes for approximate analytics. Distributed Parallel Databases 40(1): 165-200 (2022) - Koffi Messan Agbavon, Appanah Rao Appadu, Bilge Inan, Herve Michel Tenkam:
Convergence Analysis and Approximate Optimal Temporal Step Sizes for Some Finite Difference Methods Discretising Fisher's Equation. Frontiers Appl. Math. Stat. 8 (2022) - Guorui Zhu:
An Adaptive Fuzzy Neural Network Based On Progressive Gaussian Approximate Filter with Variable Step Size. Inf. Technol. Control. 51(1): 86-103 (2022) - Bónis Barcza, Ádám B. Szirmai, Katalin J. Szántó, Attila Tajti, Péter G. Szalay:
Comparison of approximate intermolecular potentials for ab initio fragment calculations on medium sized N-heterocycles. J. Comput. Chem. 43(16): 1079-1093 (2022) - Edward Farhi, Jeffrey Goldstone, Sam Gutmann, Leo Zhou:
The Quantum Approximate Optimization Algorithm and the Sherrington-Kirkpatrick Model at Infinite Size. Quantum 6: 759 (2022) - Michael Rudow, K. V. Rashmi:
Learning-Augmented Streaming Codes are Approximately Optimal for Variable-Size Messages. ISIT 2022: 474-479 - Marcio Monteiro, Ismael Seidel, Mateus Grellert, José Luís Güntzel, Leonardo Bandeira Soares, Cristina Meinhardt:
Exploring the Impacts of Multiple Kernel Sizes of Gaussian Filters Combined to Approximate Computing in Canny Edge Detection. LASCAS 2022: 1-4 - Michael Rudow, K. V. Rashmi:
Learning-Augmented Streaming Codes are Approximately Optimal for Variable-Size Messages. CoRR abs/2205.08521 (2022) - 2021
- Florian Althammer, Florian Ruf, Peter Middendorf:
Size optimization methods to approximate equivalent mechanical behaviour in thermoplastics. J. Comput. Des. Eng. 8(1): 170-188 (2021) - Jahan Claes, Wim van Dam:
Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size. Quantum 5: 542 (2021) - Ewan Davies, Will Perkins:
Approximately Counting Independent Sets of a Given Size in Bounded-Degree Graphs. ICALP 2021: 62:1-62:18 - Ewan Davies, Will Perkins:
Approximately counting independent sets of a given size in bounded-degree graphs. CoRR abs/2102.04984 (2021) - Sami Boulebnane, Ashley Montanaro:
Predicting parameters for the Quantum Approximate Optimization Algorithm for MAX-CUT from the infinite-size limit. CoRR abs/2110.10685 (2021) - 2020
- Chidong Qiu, Xinbo Wu, Changqing Xu, Xiang Qiu, Zhengyu Xue:
An Approximate Estimation Approach of Fault Size for Spalled Ball Bearing in Induction Motor by Tracking Multiple Vibration Frequencies in Current. Sensors 20(6): 1631 (2020) - 2019
- Pawel Przybylowicz:
Efficient approximate solution of jump-diffusion SDEs via path-dependent adaptive step-size control. J. Comput. Appl. Math. 350: 396-411 (2019) - Mingming Bai, Yulong Huang, Yonggang Zhang, Lyudmila Mihaylova, Jonathon A. Chambers:
A Novel Progressive Gaussian Approximate Filter with Variable Step Size Based on a Variational Bayesian Approach. ICASSP 2019: 5202-5206 - 2018
- Dong-Pil Yu, Yong-Hyuk Kim:
Is it worth to approximate fitness by machine learning?: investigation on the extensibility according to problem size. GECCO (Companion) 2018: 77-78 - Yannai A. Gonczarowski:
Bounding the menu-size of approximately optimal auctions via optimal-transport duality. STOC 2018: 123-131 - Xuebin Su, Hongzhi Wang, Jianzhong Li, Hong Gao:
MISS: Finding Optimal Sample Sizes for Approximate Analytics. CoRR abs/1807.11054 (2018) - 2017
- Li He, Nilanjan Ray, Hong Zhang:
Error bound of Nyström-approximated NCut eigenvectors and its application to training size selection. Neurocomputing 239: 130-142 (2017) - Enrique Areyan Viqueira, Amy Greenwald, Victor Naroditskiy:
On Approximate Welfare- and Revenue-Maximizing Equilibria for Size-Interchangeable Bidders. AAMAS 2017: 1466-1468 - Emmanuel Klinger, Jan Hasenauer:
A Scheme for Adaptive Selection of Population Sizes in Approximate Bayesian Computation - Sequential Monte Carlo. CMSB 2017: 128-144 - Arindam Biswas, Varunkumar Jayapaul, Venkatesh Raman, Srinivasa Rao Satti:
The Complexity of Finding (Approximate Sized) Distance-d Dominating Set in Tournaments. FAW 2017: 22-33 - Mário Lipovský, Tomás Vinar, Brona Brejová:
Approximate Abundance Histograms and Their Use for Genome Size Estimation. ITAT 2017: 27-34
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