Branding/Logomark minus Citation Combined Shape Icon/Bookmark-empty Icon/Copy Icon/Collection Icon/Close Copy 7 no author result Created with Sketch. Icon/Back Created with Sketch. Match!
Karthikeyan Natesan Ramamurthy
IBM
120Publications
11H-index
560Citations
Publications 120
Newest
Published on Jan 1, 2020
Chung-Ching Lin6
Estimated H-index: 6
(IBM),
Karthikeyan Natesan Ramamurthy11
Estimated H-index: 11
(IBM),
Sharathchandra U. Pankanti41
Estimated H-index: 41
(IBM)
To date, billions of cameras have been actively used on moving platform. Video analytics applications for camera are emerging in diverse areas. Among various video analytics applications for moving cameras, we will discuss the application of unmanned aerial vehicles (UAVs). First, we present a system for summarizing videos by automatically creating a panorama for videos, detecting and tracking moving objects in the videos. Our video summarization experiments on the UAV dataset demonstrate that w...
Ming Yu2
Estimated H-index: 2
(U of C: University of Chicago),
Karthikeyan Natesan Ramamurthy11
Estimated H-index: 11
(IBM)
+ -3 AuthorsAurelie C. Lozano14
Estimated H-index: 14
(IBM)
We consider multi-response and multi-task regression models, where the parameter matrix to be estimated is expected to have an unknown grouping structure. The groupings can be along tasks, or features, or both, the last one indicating a bi-cluster or "checkerboard" structure. Discovering this grouping structure along with parameter inference makes sense in several applications, such as multi-response Genome-Wide Association Studies (GWAS). By inferring this additional structure we can obtain val...
Published on Jul 1, 2019in IEEE Software 2.94
Rachel K. E. Bellamy22
Estimated H-index: 22
(IBM),
Kuntal Dey7
Estimated H-index: 7
(IBM)
+ 14 AuthorsSeema Nagar7
Estimated H-index: 7
(IBM)
Today, machine-learning software is used to help make decisions that affect people's lives. Some people believe that the application of such software results in fairer decisions because, unlike humans, machine-learning software generates models that are not biased. Think again. Machine-learning software is also biased, sometimes in similar ways to humans, often in different ways. While fair model- assisted decision making involves more than the application of unbiased models-consideration of app...
Karthikeyan Natesan Ramamurthy11
Estimated H-index: 11
(IBM),
Kush R. Varshney15
Estimated H-index: 15
(IBM),
Krishnan Mody1
Estimated H-index: 1
(NYU: New York University)
Anirudh Som1
Estimated H-index: 1
,
Hongjun Choi + 2 AuthorsPavan Turaga1
Estimated H-index: 1
Topological features such as persistence diagrams and their functional approximations like persistence images (PIs) have been showing substantial promise for machine learning and computer vision applications. Key bottlenecks to their large scale adoption are computational expenditure and difficulty in incorporating them in a differentiable architecture. We take an important step in this paper to mitigate these bottlenecks by proposing a novel one-step approach to generate PIs directly from the i...
Published on Jun 5, 2019in arXiv: Learning
Noel C. F. Codella13
Estimated H-index: 13
,
Michael Hind23
Estimated H-index: 23
(IBM)
+ 5 AuthorsAleksandra Mojsilovic24
Estimated H-index: 24
Using machine learning in high-stakes applications often requires predictions to be accompanied by explanations comprehensible to the domain user, who has ultimate responsibility for decisions and outcomes. Recently, a new framework for providing explanations, called TED, has been proposed to provide meaningful explanations for predictions. This framework augments training data to include explanations elicited from domain users, in addition to features and labels. This approach ensures that expl...
Min-hwan Oh (Columbia University), Peder A. Olsen22
Estimated H-index: 22
,
Karthikeyan Natesan Ramamurthy11
Estimated H-index: 11
(IBM)
Phenotyping is the process of measuring an organism's observable traits. Manual phenotyping of crops is a labor-intensive, time-consuming, costly, and error prone process. Accurate, automated, high-throughput phenotyping can relieve a huge burden in the crop breeding pipeline. In this paper, we propose a scalable, high-throughput approach to automatically count and segment panicles (heads), a key phenotype, from aerial sorghum crop imagery. Our counting approach uses the image density map obtain...
Published on Jan 1, 2019 in AAAI (National Conference on Artificial Intelligence)
Michael Hind23
Estimated H-index: 23
(IBM),
Dennis Wei (IBM)+ 5 AuthorsKush R. Varshney15
Estimated H-index: 15
(IBM)
Published on Jun 3, 2019in arXiv: Learning
Dennis Wei11
Estimated H-index: 11
,
Karthikeyan Natesan Ramamurthy11
Estimated H-index: 11
,
Flávio du Pin Calmon11
Estimated H-index: 11
This paper considers fair probabilistic classification where the outputs of primary interest are predicted probabilities, commonly referred to as scores. We formulate the problem of transforming scores to satisfy fairness constraints that are linear in conditional means of scores while minimizing the loss in utility. The same formulation can be applied both to post-process classifier outputs as well as to pre-process training data. We derive a closed-form expression for the optimal transformed s...
Published on Jan 1, 2019 in AAAI (National Conference on Artificial Intelligence)
Amanda Coston (CMU: Carnegie Mellon University), Karthikeyan Natesan Ramamurthy11
Estimated H-index: 11
(IBM)
+ 4 AuthorsSupriyo Chakraborty11
Estimated H-index: 11
(IBM)
12345678910