2 citations · 2 across the 14 of their papers we have counts for
15 papers
StratFL: Countering Covert Model Poisoning Attacks with Strategic Federated Learning
Manoj Twarakavi, Venkata Sriram Siddhardh Nadendla
Advanced persistent threats (APTs) are a major concern in federated learning (FL) deployments in critical sectors such as healthcare, and finance. Traditional defense mechanisms fa…
Fairness Perceptions in Regression-based Predictive Models
Mukund Telukunta, Venkata Sriram Siddhardh Nadendla, Morgan Stuart +1
Regression-based predictive analytics used in modern kidney transplantation is known to inherit biases from training data. This leads to social discrimination and inefficient organ…
Iterative Recommendations based on Monte Carlo Sampling and Trust Estimation in Multi-Stage Vehicular Traffic Routing Games
Doris E. M. Brown, Venkata Sriram Siddhardh Nadendla, Sajal K. Das
The shortest-time route recommendations offered by modern navigation systems fuel selfish routing in urban vehicular traffic networks and are therefore one of the main reasons for…
Driver Fatigue Prediction using Randomly Activated Neural Networks for Smart Ridesharing Platforms
Sree Pooja Akula, Mukund Telukunta, Venkata Sriram Siddhardh Nadendla
Drivers in ridesharing platforms exhibit cognitive atrophy and fatigue as they accept ride offers along the day, which can have a significant impact on the overall efficiency of th…
Learning Social Fairness Preferences from Non-Expert Stakeholder Opinions in Kidney Placement
Mukund Telukunta, Sukruth Rao, Gabriella Stickney +2
Modern kidney placement incorporates several intelligent recommendation systems which exhibit social discrimination due to biases inherited from training data. Although initial att…
TASR: A Novel Trust-Aware Stackelberg Routing Algorithm to Mitigate Traffic Congestion
Doris E. M. Brown, Venkata Sriram Siddhardh Nadendla, Sajal K. Das
Stackelberg routing platforms (SRP) reduce congestion in one-shot traffic networks by proposing optimal route recommendations to selfish travelers. Traditionally, Stackelberg routi…
Towards Inclusive Fairness Evaluation via Eliciting Disagreement Feedback from Non-Expert Stakeholders
Mukund Telukunta, Venkata Sriram Siddhardh Nadendla
Traditional algorithmic fairness notions rely on label feedback, which can only be elicited from expert critics. However, in most practical applications, several non-expert stakeho…
Convolutional Spiking Neural Networks for Detecting Anticipatory Brain Potentials Using Electroencephalogram
Nathan Lutes, Venkata Sriram Siddhardh Nadendla, K. Krishnamurthy
Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated b…
On Learning and Enforcing Latent Assessment Models using Binary Feedback from Human Auditors Regarding Black-Box Classifiers
Mukund Telukunta, Venkata Sriram Siddhardh Nadendla
Algorithmic fairness literature presents numerous mathematical notions and metrics, and also points to a tradeoff between them while satisficing some or all of them simultaneously.…
Maximizing Social Welfare in Selfish Multi-Modal Routing using Strategic Information Design for Quantal Response Travelers
Sainath Sanga, Venkata Sriram Siddhardh Nadendla, Sajal K. Das
Traditional selfish routing literature quantifies inefficiency in transportation systems with single-attribute costs using price-of-anarchy (PoA), and provides various technical ap…
Non-Comparative Fairness for Human-Auditing and Its Relation to Traditional Fairness Notions
Mukund Telukunta, Venkata Sriram Siddhardh Nadendla
Bias evaluation in machine-learning based services (MLS) based on traditional algorithmic fairness notions that rely on comparative principles is practically difficult, making it n…
On the Design of Strategic Task Recommendations for Sustainable Crowdsourcing-Based Content Moderation
Sainath Sanga, Venkata Sriram Siddhardh Nadendla
Crowdsourcing-based content moderation is a platform that hosts content moderation tasks for crowd workers to review user submissions (e.g. text, images and videos) and make decisi…
On the Identification of Fair Auditors to Evaluate Recommender Systems based on a Novel Non-Comparative Fairness Notion
Mukund Telukunta, Venkata Sriram Siddhardh Nadendla
Decision-support systems are information systems that offer support to people's decisions in various applications such as judiciary, real-estate and banking sectors. Lately, these…
A Difficulty in Controlling Blockchain Mining Costs via Cryptopuzzle Difficulty
Venkata Sriram Siddhardh Nadendla, Lav R. Varshney
Blockchain systems often employ proof-of-work consensus protocols to validate and add transactions into hashchains. These protocols stimulate competition among miners in solving cr…
On Estimating Multi-Attribute Choice Preferences using Private Signals and Matrix Factorization
Venkata Sriram Siddhardh Nadendla, Cedric Langbort
Revealed preference theory studies the possibility of modeling an agent's revealed preferences and the construction of a consistent utility function. However, modeling agent's choi…