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Shrivastava, Anshumali
129  Ergebnisse:
Personensuche X
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1

Learning Scalable Structural Representations for Link Predi..:

, In: Proceedings of the ACM on Web Conference 2024,
Zhang, Tianyi ; Yin, Haoteng ; Wei, Rongzhe.. - p. 980-991 , 2024
Link: https://dl.acm.org/doi/1..
 
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2

Near Neighbor Search for Constraint Queries:

, In: 2023 IEEE International Conference on Big Data (BigData),
Gupta, Gaurav ; Rao, Anup ; Mai, Tung... - p. 1707-1715 , 2023
Link: https://doi.org/10.1109/..
 
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3

BOLT: An Automated Deep Learning Framework for Training and..:

, In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management,
Meisburger, Nicholas ; Lakshman, Vihan ; Geordie, Benito... - p. 4738-4744 , 2023
Link: https://dl.acm.org/doi/1..
 
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4

From Research to Production: Towards Scalable and Sustainab..:

, In: Proceedings of the 17th ACM Conference on Recommender Systems,
Shrivastava, Anshumali ; Lakshman, Vihan ; Medini, Tharun... - p. 1071-1074 , 2023
Link: https://dl.acm.org/doi/1..
 
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5

BLISS: A Billion scale Index using Iterative Re-partitionin:

, In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,
Gupta, Gaurav ; Medini, Tharun ; Shrivastava, Anshumali. - p. 486-495 , 2022
Link: https://dl.acm.org/doi/1..
 
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6

ROSE: Robust Caches for Amazon Product Search:

, In: Companion Proceedings of the Web Conference 2022,
Luo, Chen ; Lakshman, Vihan ; Shrivastava, Anshumali... - p. 89-93 , 2022
Link: https://dl.acm.org/doi/1..
 
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7

Learning to Retrieve Relevant Experiences for Motion Planni..:

, In: 2022 International Conference on Robotics and Automation (ICRA),
Chamzas, Constantinos ; Cullen, Aedan ; Shrivastava, Anshumali. - p. 7233-7240 , 2022
Link: https://doi.org/10.1109/..
 
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8

Optimizing Learned Bloom Filters: How Much Should Be Learne..:

Dai, Zhenwei ; Shrivastava, Anshumali ; Reviriego, Pedro.
IEEE Embedded Systems Letters.  14 (2022)  3 - p. 123-126 , 2022
Link: https://doi.org/10.1109/..
 
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9

Solving hybrid Boolean constraints in continuous space via ..:

Kyrillidis, Anastasios ; Shrivastava, Anshumali ; Vardi, Moshe Y..
Artificial Intelligence.  299 (2021)  - p. 103559 , 2021
Link: https://doi.org/10.1016/..
 
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10

Efficient and Less Centralized Federated Learning:

, In: Machine Learning and Knowledge Discovery in Databases. Research Track; Lecture Notes in Computer Science,
Chou, Li ; Liu, Zichang ; Wang, Zhuang. - p. 772-787 , 2021
Link: https://doi.org/10.1007/..
 
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11

Active Sampling Count Sketch (ASCS) for Online Sparse Estim..:

, In: Proceedings of the 2021 International Conference on Management of Data,
Dai, Zhenwei ; Desai, Aditya ; Heckel, Reinhard. - p. 352-364 , 2021
Link: https://dl.acm.org/doi/1..
 
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12

Fast Processing and Querying of 170TB of Genomics Data via ..:

, In: Proceedings of the 2021 International Conference on Management of Data,
Gupta, Gaurav ; Yan, Minghao ; Coleman, Benjamin... - p. 2226-2234 , 2021
Link: https://dl.acm.org/doi/1..
 
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13

A One-Pass Distributed and Private Sketch for Kernel Sums w..:

, In: Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security,
Coleman, Benjamin ; Shrivastava, Anshumali - p. 3252-3265 , 2021
Link: https://dl.acm.org/doi/1..
 
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14

To Petabytes and beyond: recent advances in probabilistic a..:

Treangen, Todd J ; Shrivastava, Anshumali ; Baraniuk, Richard G...
Nucleic Acids Research.  48 (2020)  10 - p. 5217-5234 , 2020
Link: https://doi.org/10.1093/..
 
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15

Sub-linear RACE Sketches for Approximate Kernel Density Est..:

, In: Proceedings of The Web Conference 2020,
Coleman, Benjamin ; Shrivastava, Anshumali - p. 1739-1749 , 2020
Link: https://dl.acm.org/doi/1..
 
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