43 citations · 154 across the 32 of their papers we have counts for
37 papers
Capacity Achieving Codes for an Erasure Queue-Channel
Jaswanthi Mandalapu, Krishna Jagannathan, Avhishek Chatterjee +1
We consider a queue-channel model that captures the waiting time-dependent degradation of information bits as they wait to be transmitted. Such a scenario arises naturally in quant…
Finite Time Bounds for Stochastic Bounded Confidence Dynamics
Sushmitha Shree S, Avhishek Chatterjee, Krishna Jagannathan
In this era of fast and large-scale opinion formation, a mathematical understanding of opinion evolution, a.k.a. opinion dynamics, acquires importance. Linear graph-based dynamics…
Towards Maximizing Nonlinear Delay Sensitive Rewards in Queuing Systems
Sushmitha Shree S, Avijit Mandal, Avhishek Chatterjee +1
We consider maximizing the long-term average reward in a single server queue, where the reward obtained for a job is a non-increasing function of its sojourn time. The motivation b…
The Classical Capacity of Quantum Jackson Networks with Waiting Time-Dependent Erasures
Jaswanthi Mandalapu, Krishna Jagannathan
We study the fundamental limits of classical communication using quantum states that decohere as they traverse through a network of queues. We consider a network of Markovian queue…
A Survey of Risk-Aware Multi-Armed Bandits
Vincent Y. F. Tan, Prashanth L. A., Krishna Jagannathan
In several applications such as clinical trials and financial portfolio optimization, the expected value (or the average reward) does not satisfactorily capture the merits of a dru…
Stochastic Bounded Confidence Opinion Dynamics: How Far Apart Do Opinions Drift?
Sushmitha Shree S, Kishore G, Avhishek Chatterjee +1
In this era of fast and large-scale opinion formation, a mathematical understanding of opinion evolution, a.k.a. opinion dynamics, is especially important. Linear graph-based dynam…
Online Estimation and Optimization of Utility-Based Shortfall Risk
Vishwajit Hegde, Arvind S. Menon, L. A. Prashanth +1
Utility-Based Shortfall Risk (UBSR) is a risk metric that is increasingly popular in financial applications, owing to certain desirable properties that it enjoys. We consider the p…
Queue-Channel Capacities with Generalized Amplitude Damping
Vikesh Siddhu, Avhishek Chatterjee, Krishna Jagannathan +2
The generalized amplitude damping channel (GADC) is considered an important model for quantum communications, especially over optical networks. We make two salient contributions in…
Statistically Robust, Risk-Averse Best Arm Identification in Multi-Armed Bandits
Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan
Traditional multi-armed bandit (MAB) formulations usually make certain assumptions about the underlying arms' distributions, such as bounds on the support or their tail behaviour.…
Bandit algorithms: Letting go of logarithmic regret for statistical robustness
Kumar Ashutosh, Jayakrishnan Nair, Anmol Kagrecha +1
We study regret minimization in a stochastic multi-armed bandit setting and establish a fundamental trade-off between the regret suffered under an algorithm, and its statistical ro…
Constrained regret minimization for multi-criterion multi-armed bandits
Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan
We consider a stochastic multi-armed bandit setting and study the problem of constrained regret minimization over a given time horizon. Each arm is associated with an unknown, poss…
A Framework for End-to-End Deep Learning-Based Anomaly Detection in Transportation Networks
Neema Davis, Gaurav Raina, Krishna Jagannathan
We develop an end-to-end deep learning-based anomaly detection model for temporal data in transportation networks. The proposed EVT-LSTM model is derived from the popular LSTM (Lon…
LSTM-Based Anomaly Detection: Detection Rules from Extreme Value Theory
Neema Davis, Gaurav Raina, Krishna Jagannathan
In this paper, we explore various statistical techniques for anomaly detection in conjunction with the popular Long Short-Term Memory (LSTM) deep learning model for transportation…
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards
Anmol Kagrecha, Jayakrishnan Nair, Krishna Jagannathan
Classical multi-armed bandit problems use the expected value of an arm as a metric to evaluate its goodness. However, the expected value is a risk-neutral metric. In many applicati…
The Classical Capacity of Additive Quantum Queue-Channels
Prabha Mandayam, Krishna Jagannathan, Avhishek Chatterjee
We consider a setting where a stream of qubits is processed sequentially. We derive fundamental limits on the rate at which classical information can be transmitted using qubits th…
On Minimizing the Maximum Age-of-Information For Wireless Erasure Channels
Arunabh Srivastava, Abhishek Sinha, Krishna Jagannathan
Age-of-Information (AoI) is a recently proposed metric for quantifying the freshness of information from the UE's perspective in a communication network. Recently, Kadota et al. [1…
Grids versus Graphs: Partitioning Space for Improved Taxi Demand-Supply Forecasts
Neema Davis, Gaurav Raina, Krishna Jagannathan
Accurate taxi demand-supply forecasting is a challenging application of ITS (Intelligent Transportation Systems), due to the complex spatial and temporal patterns. We investigate t…
Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
Prashanth L. A., Krishna Jagannathan, Ravi Kumar Kolla
Conditional Value-at-Risk (CVaR) is a widely used risk metric in applications such as finance. We derive concentration bounds for CVaR estimates, considering separately the cases o…
Taxi Demand-Supply Forecasting: Impact of Spatial Partitioning on the Performance of Neural Networks
Neema Davis, Gaurav Raina, Krishna Jagannathan
In this paper, we investigate the significance of choosing an appropriate tessellation strategy for a spatio-temporal taxi demand-supply modeling framework. Our study compares (i)…
Concentration bounds for empirical conditional value-at-risk: The unbounded case
Ravi Kumar Kolla, Prashanth L. A., Sanjay P. Bhat +1
In several real-world applications involving decision making under uncertainty, the traditional expected value objective may not be suitable, as it may be necessary to control loss…
Taxi demand forecasting: A HEDGE based tessellation strategy for improved accuracy
Neema Davis, Gaurav Raina, Krishna Jagannathan
A key problem in location-based modeling and forecasting lies in identifying suitable spatial and temporal resolutions. In particular, judicious spatial partitioning can play a sig…
Impact of delayed acceleration feedback on the classical car-following model
Gopal Krishna Kamath, Krishna Jagannathan, Gaurav Raina
Delayed feedback plays a vital role in determining the qualitative dynamical properties of a platoon of vehicles driving on a straight road. Motivated by the positive impact of Del…
Qubits through Queues: The Capacity of Channels with Waiting Time Dependent Errors
Avhishek Chatterjee, Krishna Jagannathan, Prabha Mandayam
We consider a setting where qubits are processed sequentially, and derive fundamental limits on the rate at which classical information can be transmitted using quantum states that…
Caching under Content Freshness Constraints
Pawan Poojary, Sharayu Moharir, Krishna Jagannathan
Several real-time delay-sensitive applications pose varying degrees of freshness demands on the requested content. The performance of cache replacement policies that are agnostic t…