Kaushik Sinha - RankMe

49 papers A* 10A 1B 4C 3Journal 19Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Optimal rates for density and mode estimation with expand-and-sparsify representations. CoRR Kaushik Sinha, Christopher Tosh
2026	J	`jnl`	Regionalize and Scale: Amazon's Fulfillment Network Design for Faster and Cheaper Delivery. INFORMS J. Appl. Anal. Amitabh Sinha, Jeremy Agte, Russell Allgor, Cristiana L. Lara, Ashish Agiwal, Semih Atakan, Lourdes Campo, Tolga Cezik, Daniel Chongli Chen, Qi Chen, Jesse Fischer, Eitan Gor, Nader Kabbani, Ryan Kennedy, Kaushik Krishnan, Yuan Li, Shahbaaz Mubeen Mamadapur, Tanmay Mathur, Nick McCabe, David Mildebrath, Eric Powell, Andrea Qualizza, Denton Schroeder, Nityansh Seth, Xiaoyan Si, Kaushik Sinha, Darren Stegner, Jun Xiao, Ling Zhang, Shanshan Zhang, Jikai Zou
2024	A*	`conf`	Non-parametric classification via expand-and-sparsify representation. NeurIPS Kaushik Sinha
2022	J	`jnl`	Domain Mapping Matrix-Based Metric for Measuring System Design Complexity. IEEE Trans. Engineering Management Sungjoon Jung, Kaushik Sinha, Eun Suk Suh
2022	A*	`conf`	Federated Nearest Neighbor Classification with a Colony of Fruit-Flies. AAAI Parikshit Ram, Kaushik Sinha
2021	J	`jnl`	Federated Nearest Neighbor Classification with a Colony of Fruit-Flies: With Supplement. CoRR Parikshit Ram, Kaushik Sinha
2021	A*	`conf`	Fruit-fly Inspired Neighborhood Encoding for Classification. KDD Kaushik Sinha, Parikshit Ram
2021	J	`jnl`	Random projection-based auxiliary information can improve tree-based nearest neighbor search. Inf. Sci. Omid Keivani, Kaushik Sinha
2020	J	`jnl`	Design structure matrix-based modularization approach for complex systems with multiple design constraints. Syst. Eng. Kaushik Sinha, Seok-Youn Han, Eun Suk Suh
2020	—	`conf`	IBeaconMap: Automated Indoor Space Representation for Beacon-Based Wayfinding. ICCHP (1) Seyed Ali Cheraghi, Vinod Namboodiri, Kaushik Sinha
2020	J	`jnl`	Neural Neighborhood Encoding for Classification. CoRR Kaushik Sinha, Parikshit Ram
2019	A*	`conf`	Revisiting kd-tree for Nearest Neighbor Search. KDD Parikshit Ram, Kaushik Sinha
2018	J	`jnl`	IBeaconMap: Automated Indoor Space Representation for Beacon-Based Wayfinding. CoRR Seyed Ali Cheraghi, Vinod Namboodiri, Kaushik Sinha
2018	J	`jnl`	Improved maximum inner product search with better theoretical guarantee using randomized partition trees. Mach. Learn. Omid Keivani, Kaushik Sinha, Parikshit Ram
2018	A*	`conf`	Improved nearest neighbor search using auxiliary information and priority functions. ICML Omid Keivani, Kaushik Sinha
2018	A*	`conf`	K-means clustering using random matrix sparsification. ICML Kaushik Sinha
2018	B	`conf`	Robotic Understanding of Scene Contents and Spatial Constraints. ICSR Dustin Wilson, Fujian Yan, Kaushik Sinha, Hongsheng He
2017	B	`conf`	A novel machine learning framework for phenotype prediction based on genome-wide DNA methylation data. IJCNN Vinay Vittal Karagod, Kaushik Sinha
2017	B	`conf`	A support vector machine approach to identification of proteins relevant to learning in a mouse model of Down Syndrome. IJCNN Tara Eicher, Kaushik Sinha
2017	B	`conf`	Improved maximum inner product search with better theoretical guarantees. IJCNN Omid Keivani, Kaushik Sinha, Parikshit Ram
2017	A	`conf`	Sparse Randomized Partition Trees for Nearest Neighbor Search. AISTATS Kaushik Sinha, Omid Keivani
2016	—	`conf`	Complexity Management for Engineered Systems Using System Value Definition. CSDM Kaushik Sinha, Narek R. Shougarian, Olivier L. de Weck
2016	J	`jnl`	Empirical Validation of Structural Complexity Metric and Complexity Management for Engineering Systems. Syst. Eng. Kaushik Sinha, Olivier L. de Weck
2016	—	`conf`	Exploring Early Stage Cost-Estimation Methods Using Off-the-Shelf Tools: A Preliminary Study. CSDM Haifeng Zhu, Narek R. Shougarian, Greg Ojard, Kaushik Sinha, Oliver de Weck, Eileen Arnold
2016	J	`jnl`	Matrix Energy as a Measure of Topological Complexity of a Graph. CoRR Kaushik Sinha, Olivier L. de Weck
2015	—	`conf`	Fast £1-norm Nearest Neighbor Search Using A Simple Variant of Randomized Partition Tree. INNS Conference on Big Data Kaushik Sinha
2015	J	`jnl`	Polynomial Learning of Distribution Families. SIAM J. Comput. Mikhail Belkin, Kaushik Sinha
2015	J	`jnl`	Randomized Partition Trees for Nearest Neighbor Search. Algorithmica Sanjoy Dasgupta, Kaushik Sinha
2014	C	`conf`	LSH vs Randomized Partition Trees: Which One to Use for Nearest Neighbor Search? ICMLA Kaushik Sinha
2014	—	`ch.`	Semi-Supervised Learning. Data Classification: Algorithms and Applications Kaushik Sinha
2013	J	`jnl`	A near-optimal algorithm for differentially-private principal components. J. Mach. Learn. Res. Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha
2013	—	`conf`	A network-based structural complexity metric for engineered complex systems. SysCon Kaushik Sinha, Olivier L. de Weck
2013	J	`jnl`	Randomized partition trees for exact nearest neighbor search CoRR Sanjoy Dasgupta, Kaushik Sinha
2013	A*	`conf`	Randomized partition trees for exact nearest neighbor search. COLT Sanjoy Dasgupta, Kaushik Sinha
2012	J	`jnl`	Near-Optimal Algorithms for Differentially-Private Principal Components CoRR Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha
2012	—	`conf`	Near-optimal Differentially Private Principal Components. NIPS Kamalika Chaudhuri, Anand D. Sarwate, Kaushik Sinha
2010	J	`jnl`	Polynomial Learning of Distribution Families CoRR Mikhail Belkin, Kaushik Sinha
2010	A*	`conf`	Polynomial Learning of Distribution Families. FOCS Mikhail Belkin, Kaushik Sinha
2010	A*	`conf`	Toward Learning Gaussian Mixtures with Arbitrary Separation. COLT Mikhail Belkin, Kaushik Sinha
2009	J	`jnl`	Learning Gaussian Mixtures with Arbitrary Separation CoRR Mikhail Belkin, Kaushik Sinha
2009	—	`conf`	Semi-Supervised Learning Using Sparse Eigenfunction Bases. AAAI Fall Symposium: Manifold Learning and Its Applications Kaushik Sinha, Mikhail Belkin
2009	—	`conf`	Semi-supervised Learning using Sparse Eigenfunction Bases. NIPS Kaushik Sinha, Mikhail Belkin
2007	J	`jnl`	A Decentralized Approach to Discrete Optimization via Simulation: Application to Network Flow. Oper. Res. Alfredo García, Stephen D. Patek, Kaushik Sinha
2007	—	`conf`	The Value of Labeled and Unlabeled Examples when the Model is Imperfect. NIPS Kaushik Sinha, Mikhail Belkin
2006	C	`conf`	Exploratory Tools for FollowUp Studies to Microarray Experiments. BIBE Kaushik Sinha, Ruoming Jin, Gagan Agrawal, Helen Piontkivska
2005	—	`conf`	A framework to support multiple query optimization for complex mining tasks. MDM/KDD Ruoming Jin, Kaushik Sinha, Gagan Agrawal
2005	—	`conf`	Learning Layouts of Biological Datasets Semi-automatically. DILS Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agrawal
2005	A*	`conf`	Simultaneous optimization of complex mining tasks with a knowledgeable cache. KDD Ruoming Jin, Kaushik Sinha, Gagan Agrawal
2005	C	`conf`	Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets. BIBE Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agrawal