default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDKaushik Sinha
Person information
SPARQL queries 
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2022
[j9]Sungjoon Jung, Kaushik Sinha, Eun Suk Suh
:
Domain Mapping Matrix-Based Metric for Measuring System Design Complexity. IEEE Trans. Engineering Management 69(5): 2187-2195 (2022)- [c28]Parikshit Ram, Kaushik Sinha:
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies. AAAI 2022: 8036-8044 - 2021
- [j8]Omid Keivani, Kaushik Sinha:
Random projection-based auxiliary information can improve tree-based nearest neighbor search. Inf. Sci. 546: 526-542 (2021) - [c27]Kaushik Sinha, Parikshit Ram:
Fruit-fly Inspired Neighborhood Encoding for Classification. KDD 2021: 1470-1480 - [i8]Parikshit Ram, Kaushik Sinha:
Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement. CoRR abs/2112.07157 (2021) - 2020
- [j7]Kaushik Sinha, Seok-Youn Han, Eun Suk Suh:
Design structure matrix-based modularization approach for complex systems with multiple design constraints. Syst. Eng. 23(2): 211-220 (2020) - [c26]Seyed Ali Cheraghi, Vinod Namboodiri, Kaushik Sinha:
IBeaconMap: Automated Indoor Space Representation for Beacon-Based Wayfinding. ICCHP (1) 2020: 105-113 - [i7]Kaushik Sinha, Parikshit Ram:
Neural Neighborhood Encoding for Classification. CoRR abs/2008.08685 (2020)
2010 – 2019
- 2019
- [c25]Parikshit Ram, Kaushik Sinha:
Revisiting kd-tree for Nearest Neighbor Search. KDD 2019: 1378-1388 - 2018
- [j6]Omid Keivani, Kaushik Sinha, Parikshit Ram:
Improved maximum inner product search with better theoretical guarantee using randomized partition trees. Mach. Learn. 107(6): 1069-1094 (2018) - [c24]Omid Keivani, Kaushik Sinha:
Improved nearest neighbor search using auxiliary information and priority functions. ICML 2018: 2578-2586 - [c23]Kaushik Sinha:
K-means clustering using random matrix sparsification. ICML 2018: 4691-4699 - [c22]Dustin Wilson, Fujian Yan, Kaushik Sinha, Hongsheng He:
Robotic Understanding of Scene Contents and Spatial Constraints. ICSR 2018: 93-102 - [i6]Seyed Ali Cheraghi, Vinod Namboodiri, Kaushik Sinha:
IBeaconMap: Automated Indoor Space Representation for Beacon-Based Wayfinding. CoRR abs/1802.05735 (2018) - 2017
- [c21]Kaushik Sinha, Omid Keivani:
Sparse Randomized Partition Trees for Nearest Neighbor Search. AISTATS 2017: 681-689 - [c20]Vinay Vittal Karagod, Kaushik Sinha:
A novel machine learning framework for phenotype prediction based on genome-wide DNA methylation data. IJCNN 2017: 1657-1664 - [c19]Omid Keivani, Kaushik Sinha, Parikshit Ram:
Improved maximum inner product search with better theoretical guarantees. IJCNN 2017: 2927-2934 - [c18]Tara Eicher, Kaushik Sinha:
A support vector machine approach to identification of proteins relevant to learning in a mouse model of Down Syndrome. IJCNN 2017: 3391-3398 - 2016
- [j5]Kaushik Sinha, Olivier L. de Weck:
Empirical Validation of Structural Complexity Metric and Complexity Management for Engineering Systems. Syst. Eng. 19(3): 193-206 (2016) - [c17]Kaushik Sinha, Narek R. Shougarian, Olivier L. de Weck:
Complexity Management for Engineered Systems Using System Value Definition. CSDM 2016: 155-170 - [c16]Haifeng Zhu, Narek R. Shougarian, Greg Ojard, Kaushik Sinha, Oliver de Weck, Eileen Arnold:
Exploring Early Stage Cost-Estimation Methods Using Off-the-Shelf Tools: A Preliminary Study. CSDM 2016: 251 - [i5]Kaushik Sinha, Olivier L. de Weck:
Matrix Energy as a Measure of Topological Complexity of a Graph. CoRR abs/1608.08456 (2016) - 2015
- [j4]Sanjoy Dasgupta, Kaushik Sinha:
Randomized Partition Trees for Nearest Neighbor Search. Algorithmica 72(1): 237-263 (2015) - [j3]Mikhail Belkin, Kaushik Sinha:
Polynomial Learning of Distribution Families. SIAM J. Comput. 44(4): 889-911 (2015) - [c15]Kaushik Sinha:
Fast £1-norm Nearest Neighbor Search Using A Simple Variant of Randomized Partition Tree. INNS Conference on Big Data 2015: 64-73 - 2014
- [c14]Kaushik Sinha:
LSH vs Randomized Partition Trees: Which One to Use for Nearest Neighbor Search? ICMLA 2014: 41-46 - [p1]Kaushik Sinha:
Semi-Supervised Learning. Data Classification: Algorithms and Applications 2014: 511-536 - 2013
- [j2]Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha:
A near-optimal algorithm for differentially-private principal components. J. Mach. Learn. Res. 14(1): 2905-2943 (2013) - [c13]Sanjoy Dasgupta, Kaushik Sinha:
Randomized partition trees for exact nearest neighbor search. COLT 2013: 317-337 - [c12]Kaushik Sinha, Olivier L. de Weck:
A network-based structural complexity metric for engineered complex systems. SysCon 2013: 426-430 - [i4]Sanjoy Dasgupta, Kaushik Sinha:
Randomized partition trees for exact nearest neighbor search. CoRR abs/1302.1948 (2013) - 2012
- [c11]Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha:
Near-optimal Differentially Private Principal Components. NIPS 2012: 998-1006 - [i3]Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha:
Near-Optimal Algorithms for Differentially-Private Principal Components. CoRR abs/1207.2812 (2012) - 2010
- [c10]Mikhail Belkin, Kaushik Sinha:
Toward Learning Gaussian Mixtures with Arbitrary Separation. COLT 2010: 407-419 - [c9]Mikhail Belkin, Kaushik Sinha:
Polynomial Learning of Distribution Families. FOCS 2010: 103-112 - [i2]Mikhail Belkin, Kaushik Sinha:
Polynomial Learning of Distribution Families. CoRR abs/1004.4864 (2010)
2000 – 2009
- 2009
- [c8]Kaushik Sinha, Mikhail Belkin:
Semi-Supervised Learning Using Sparse Eigenfunction Bases. AAAI Fall Symposium: Manifold Learning and Its Applications 2009 - [c7]Kaushik Sinha, Mikhail Belkin:
Semi-supervised Learning using Sparse Eigenfunction Bases. NIPS 2009: 1687-1695 - [i1]Mikhail Belkin, Kaushik Sinha:
Learning Gaussian Mixtures with Arbitrary Separation. CoRR abs/0907.1054 (2009) - 2007
- [j1]Alfredo García, Stephen D. Patek, Kaushik Sinha:
A Decentralized Approach to Discrete Optimization via Simulation: Application to Network Flow. Oper. Res. 55(4): 717-732 (2007) - [c6]Kaushik Sinha, Mikhail Belkin:
The Value of Labeled and Unlabeled Examples when the Model is Imperfect. NIPS 2007: 1361-1368 - 2006
- [c5]Kaushik Sinha, Ruoming Jin, Gagan Agrawal, Helen Piontkivska:
Exploratory Tools for FollowUp Studies to Microarray Experiments. BIBE 2006: 81-85 - 2005
- [c4]Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agrawal:
Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets. BIBE 2005: 177-184 - [c3]Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agrawal:
Learning Layouts of Biological Datasets Semi-automatically. DILS 2005: 31-45 - [c2]Ruoming Jin, Kaushik Sinha, Gagan Agrawal:
A framework to support multiple query optimization for complex mining tasks. MDM@KDD 2005: 23-32 - [c1]Ruoming Jin, Kaushik Sinha, Gagan Agrawal:
Simultaneous optimization of complex mining tasks with a knowledgeable cache. KDD 2005: 600-605
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-01-21 00:24 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
