Folgen
Krishna Jagannathan
Krishna Jagannathan
Professor, Department of Electrical Engineering, IIT Madras
Bestätigte E-Mail-Adresse bei ee.iitm.ac.in - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Non-cooperative spectrum access: the dedicated vs. free spectrum choice
K Jagannathan, I Menache, G Zussman, E Modiano
Proceedings of the Twelfth ACM International Symposium on Mobile Ad Hoc …, 2011
862011
A multi-level clustering approach for forecasting taxi travel demand
N Davis, G Raina, K Jagannathan
2016 IEEE 19th international conference on intelligent transportation …, 2016
832016
Collaborative learning of stochastic bandits over a social network
RK Kolla, K Jagannathan, A Gopalan
IEEE/ACM Transactions on Networking 26 (4), 1782-1795, 2018
792018
Concentration bounds for empirical conditional value-at-risk: The unbounded case
RK Kolla, LA Prashanth, SP Bhat, K Jagannathan
Operations Research Letters 47 (1), 16-20, 2019
562019
Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
LA Prashanth, K Jagannathan, RK Kolla
Proceedings of the 37th International Conference on Machine Learning, 5577-5586, 2020
512020
Distribution oblivious, risk-aware algorithms for multi-armed bandits with unbounded rewards.
A Kagrecha, J Nair, KP Jagannathan
NeurIPS, 11269-11278, 2019
462019
Taxi demand forecasting: A HEDGE-based tessellation strategy for improved accuracy
N Davis, G Raina, K Jagannathan
IEEE Transactions on Intelligent Transportation Systems 19 (11), 3686-3697, 2018
462018
Delay analysis of maximum weight scheduling in wireless ad hoc networks
LB Le, K Jagannathan, E Modiano
2009 43rd Annual Conference on Information Sciences and Systems, 389-394, 2009
452009
Grids versus graphs: Partitioning space for improved taxi demand-supply forecasts
N Davis, G Raina, K Jagannathan
IEEE Transactions on Intelligent Transportation Systems 22 (10), 6526-6535, 2020
402020
Queue-length asymptotics for generalized max-weight scheduling in the presence of heavy-tailed traffic
K Jagannathan, M Markakis, E Modiano, JN Tsitsiklis
IEEE/ACM Transactions on Networking 20 (4), 1096-1111, 2011
392011
A framework for end-to-end deep learning-based anomaly detection in transportation networks
N Davis, G Raina, K Jagannathan
Transportation research interdisciplinary perspectives 5, 100112, 2020
382020
A state action frequency approach to throughput maximization over uncertain wireless channels
K Jagannathan, S Mannor, I Menache, E Modiano
Internet Mathematics 9 (2-3), 136-160, 2013
352013
Congestion costs incurred on Indian Roads: A case study for New Delhi
N Davis, HR Joseph, G Raina, K Jagannathan
arXiv preprint arXiv:1708.08984, 2017
272017
Scheduling of multi-antenna broadcast systems with heterogeneous users
K Jagannathan, S Borst, P Whiting, E Modiano
IEEE Journal on Selected Areas in Communications 25 (7), 1424-1434, 2007
262007
Efficient scheduling of multi-user multi-antenna systems
KP Jagannathan, S Borst, P Whiting, E Modiano
2006 4th International Symposium on Modeling and Optimization in Mobile, Ad …, 2006
232006
Car-following models with delayed feedback: local stability and Hopf bifurcation
GK Kamath, K Jagannathan, G Raina
2015 53rd Annual Allerton Conference on Communication, Control, and …, 2015
222015
Queue-Aware Optimal Resource Allocation for the LTE Downlink With BestSubband Feedback
H Ahmed, K Jagannathan, S Bhashyam
IEEE Transactions on Wireless Communications 14 (9), 4923-4933, 2015
192015
Bandit algorithms: Letting go of logarithmic regret for statistical robustness
K Ashutosh, J Nair, A Kagrecha, K Jagannathan
International Conference on Artificial Intelligence and Statistics, 622-630, 2021
172021
Stability, convergence and Hopf bifurcation analyses of the classical car-following model
GK Kamath, K Jagannathan, G Raina
Nonlinear Dynamics 96, 185-204, 2019
172019
Adaptive CSMA under the SINR model: Efficient approximation algorithms for throughput and utility maximization
PS Swamy, RK Ganti, K Jagannathan
IEEE/ACM Transactions on Networking 25 (4), 1968-1981, 2017
172017
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20