Sampath Kannan
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View article: Full-head segmentation of MRI with abnormal brain anatomy: model and data release
Full-head segmentation of MRI with abnormal brain anatomy: model and data release Open
We are releasing a new state-of-the-art tool for whole-head MRI segmentation in abnormal anatomy, along with the largest volume of labeled clinical head MRIs, including labels for nonbrain structures. Together, the model and data may serve…
View article: Counting How the Seconds Count: Understanding Algorithm-User Interplay in TikTok via ML-driven Analysis of Video Content
Counting How the Seconds Count: Understanding Algorithm-User Interplay in TikTok via ML-driven Analysis of Video Content Open
Short video streaming systems such as TikTok, Youtube Shorts, Instagram Reels, etc have reached billions of active users. At the core of such systems is a (proprietary) recommendation algorithm which recommends a sequence of videos to each…
View article: Detection of misbehavior activity as copycat nodes in wireless sensor networks to enhance the network security
Detection of misbehavior activity as copycat nodes in wireless sensor networks to enhance the network security Open
The first relies on a distributed hash table (DHT), within which the Chord algorithmic program is employed to find cloned nodes. Every Node is given a random key, and before transmission information, it should offer its key that is checked…
View article: Fair Prediction with Endogenous Behavior
Fair Prediction with Endogenous Behavior Open
There is increasing regulatory interest in whether machine learning algorithms deployed in consequential domains (e.g. in criminal justice) treat different demographic groups "fairly." However, there are several proposed notions of fairnes…
View article: Service in Your Neighborhood: Fairness in Center Location
Service in Your Neighborhood: Fairness in Center Location Open
When selecting locations for a set of centers, standard clustering algorithms may place unfair burden on some individuals and neighborhoods. We formulate a fairness concept that takes local population densities into account. In particular,…
View article: Sublinear Algorithms and Lower Bounds for Metric TSP Cost Estimation.
Sublinear Algorithms and Lower Bounds for Metric TSP Cost Estimation. Open
We consider the problem of designing sublinear time algorithms for estimating the cost of minimum metric traveling salesman (TSP) tour. Specifically, given access to a n × n distance matrix D that specifies pairwise distances between n poi…
View article: Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases
Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases Open
The aim of this paper is to introduce an effective fuzzy clustering technique based kernel function to find appropriate subgroups in heterogeneous databases. This paper introduces the effective fuzzy clustering that incorporates weighted b…
View article: Counting the Number of Non-Equivalent Classes of Fuzzy Matrices Using Combinatorial Techniques
Counting the Number of Non-Equivalent Classes of Fuzzy Matrices Using Combinatorial Techniques Open
The novelty of this paper is to construct the explicit combinatorial formula for the number of all distinct fuzzy matrices of finite order, which leads us to invent a new sequence. In order to achieve this new sequence, we analyze the beha…
View article: A Center in Your Neighborhood: Fairness in Facility Location
A Center in Your Neighborhood: Fairness in Facility Location Open
When selecting locations for a set of facilities, standard clustering algorithms may place unfair burden on some individuals and neighborhoods. We formulate a fairness concept that takes local population densities into account. In particul…
View article: Effect of Kernel Learning in Unsupervised Learning for Clustering High Dimensional Databases
Effect of Kernel Learning in Unsupervised Learning for Clustering High Dimensional Databases Open
This paper reviews the effectiveness of kernel learning in unsupervised data analysis using clustering. Cluster analysis is an explorative data analysis tool that assists in discovering hidden patterns or natural grouping and has many effe…
View article: Game Theory in AI, Logic, and Algorithms (Dagstuhl Seminar 17111)
Game Theory in AI, Logic, and Algorithms (Dagstuhl Seminar 17111) Open
This report documents the program and the outcomes of Dagstuhl Seminar 17111 "Game Theory in AI, Logic, and Algorithms".