M. Vidyasagar - RankMe

58 papers A* 11B 3C 3Journal 21Unranked 19

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications. CoRR Rajeeva Laxman Karandikar, M. Vidyasagar
2023	J	`jnl`	Convergence of stochastic approximation via martingale and converse Lyapunov methods. Math. Control. Signals Syst. M. Vidyasagar
2022	—	`conf`	A New Converse Lyapunov Theorem for Global Exponential Stability and Applications to Stochastic Approximation. CDC M. Vidyasagar
2022	J	`jnl`	Convergence of Stochastic Approximation via Martingale and Converse Lyapunov Methods. CoRR M. Vidyasagar
2021	J	`jnl`	Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning. CoRR Rajeeva Laxman Karandikar, M. Vidyasagar
2020	J	`jnl`	Modelling a pandemic with asymptomatic patients, impact of lockdown and herd immunity, with applications to SARS-CoV-2. Annu. Rev. Control. Santosh Ansumali, Shaurya Kaushal, Aloke Kumar, Meher K. Prakash, M. Vidyasagar
2020	C	`conf`	Recent Advances in Reinforcement Learning. ACC M. Vidyasagar
2019	J	`jnl`	Editorial to the Special Issue of L-CSS on Control and Network Theory for Biological Systems. IEEE Control. Syst. Lett. Murat Arcak, Franco Blanchini, M. Vidyasagar
2017	—	`conf`	Integrating biological data across multiple platforms using importance-weighted transfer learning and applications to breast cancer data sets. CCTA Hema Kumari Achanta, Burook Misganaw, M. Vidyasagar
2016	C	`conf`	A transfer learning approach for integrating biological data across platforms. ACC Hema Kumari Achanta, Burook Misganaw, M. Vidyasagar
2016	—	`conf`	A tutorial introduction to compressed sensing. CDC M. Vidyasagar
2014	—	`conf`	Inferring Gene Regulatory Networks with Sparse Bayesian Learning and phi-mixing coefficient. ECC Nitin K. Singh, M. Vidyasagar
2013	—	`conf`	On the computation of mixing coefficients between discrete-valued random variables. ASCC Mehmet Eren Ahsen, M. Vidyasagar
2012	—	`conf`	A new feature selection algorithm for two-class classification problems and application to endometrial cancer. CDC Mehmet Eren Ahsen, Nitin K. Singh, Todd P. Boren, M. Vidyasagar, Michael A. White
2012	—	`conf`	A novel application of mixing coefficients for reverse-engineering gene interaction networks. Allerton Conference Nitin K. Singh, Mehmet Eren Ahsen, Shiva Mankala, M. Vidyasagar, Michael A. White
2012	—	`conf`	Inferring weighted and directed gene interaction networks from gene expression data using the phi-mixing coefficient. GENSiPS Nitin K. Singh, Mehmet Eren Ahsen, Shiva Mankala, M. Vidyasagar, Michael A. White
2011	—	`conf`	A metric between probability distributions on finite sets of different cardinalities. CDC/ECC M. Vidyasagar
2011	—	`conf`	Optimal order reduction of probability distributions by maximizing mutual information. CDC/ECC M. Vidyasagar
2011	J	`jnl`	The complete realization problem for hidden Markov models: a survey and some new results. Math. Control. Signals Syst. M. Vidyasagar
2009	—	`ch.`	Learning, System Identification, and Complexity. Encyclopedia of Complexity and Systems Science M. Vidyasagar
2008	J	`jnl`	Guest Editorial - Special Issue on Systems Biology. IEEE Trans. Autom. Control. Mustafa Khammash, Claire J. Tomlin, M. Vidyasagar
2007	—	`conf`	A Unified Approach to Encoding and Classification Using Bimodal Projection-Based Features. ICCTA Dipti Deodhare, M. Vidyasagar, M. Narasimha Murty
2007	—	`conf`	Bounds on the kullback-leibler divergence rate between hidden markov models. CDC M. Vidyasagar
2007	—	`conf`	Predicting protein-protein interactions in E. coli using machine learning methods. CDC Kshama Goyal, M. Vidyasagar
2006	B	`conf`	Bimodal Projection-based Features for Pattern Classification. IJCNN Dipti Deodhare, M. Vidyasagar, M. Narasimha Murty
2006	—	`conf`	The 4M (Mixed Memory Markov Model) Algorithm for Finding Genes from Prokaryote Genomes. CDC M. Vidyasagar
2005	—	`conf`	Convergence of Empirical Means with Alpha-Mixing Input Sequences, and an Application to PAC Learning. CDC/ECC M. Vidyasagar
2005	—	`conf`	The Realization Problem for Hidden Markov Models: The Complete Realization Problem. CDC/ECC M. Vidyasagar
2003	—	`conf`	Some challenges in computational biology. ECC M. Vidyasagar
2003	—	`conf`	Synthesis of hidden Markov models based on finite sample paths and applications to computational biology. ECC M. Vidyasagar
2001	J	`jnl`	Probabilistic solutions to some NP-hard matrix problems. Autom. M. Vidyasagar, Vincent D. Blondel
2001	J	`jnl`	Randomized algorithms for robust controller synthesis using statistical learning theory. Autom. M. Vidyasagar
2000	C	`conf`	Learning with prior information. ISCAS Marco C. Campi, M. Vidyasagar
2000	J	`jnl`	Some contributions to fixed-distribution learning theory. IEEE Trans. Autom. Control. M. Vidyasagar, Sanjeev R. Kulkarni
1998	J	`jnl`	Synthesis of fault-tolerant feedforward neural networks using minimax optimization. IEEE Trans. Neural Networks Dipti Deodhare, M. Vidyasagar, S. Sathiya Keerthi
1997	J	`jnl`	Learning decision rules for pattern classification under a family of probability measures. IEEE Trans. Inf. Theory Sanjeev R. Kulkarni, M. Vidyasagar
1996	J	`jnl`	A Brief History of the Graph Topology Eur. J. Control M. Vidyasagar
1993	—	`conf`	Convergence of higher-order neural networks with modified updating. ICNN M. Vidyasagar
1992	A*	`conf`	A new parallelogram linkage configuration for gravity compensation using torsional springs. ICRA Ajay Gopalswamy, Pramod Gupta, M. Vidyasagar
1991	A*	`conf`	New techniques for H ICRA David Vinke, M. Vidyasagar
1991	A*	`conf`	Passivity of flexible beam transfer functions with modified outputs. ICRA Hemanshu Roy Pota, M. Vidyasagar
1991	A*	`conf`	Path planning for moving a point object amidst unknown obstacles in a plane: the universal lower bound on the worst path lengths and a classification of algorithms. ICRA A. Sankaranarayanan, M. Vidyasagar
1990	A*	`conf`	A new path planning algorithm for moving a point object amidst unknown obstacles in a plane. ICRA A. Sankaranarayanan, M. Vidyasagar
1990	B	`conf`	An analysis of the flows of neural networks with linear interconnections. IJCNN M. Vidyasagar
1990	B	`conf`	Improved neural networks for analog to digital conversion. IJCNN M. Vidyasagar
1990	A*	`conf`	Passive control of a single flexible link. ICRA David Wang, M. Vidyasagar
1989	A*	`conf`	Transfer functions for a single flexible link. ICRA David Wang, M. Vidyasagar
1987	A*	`conf`	Control of a flexible beam for optimum step response. ICRA David Wang, M. Vidyasagar
1987	A*	`conf`	Control of a flexible robot arm with bounded input: Optimum step responses. ICRA I. Y. Shung, M. Vidyasagar
1987	J	`jnl`	Parametric conditions for stability of reduced-order linear time-varying control systems. Autom. C. C. H. Ma, M. Vidyasagar
1987	A*	`conf`	Some qualitative results on the collision-free joint space of a planar n-DOF linkage. ICRA Y. C. Chen, M. Vidyasagar
1987	J	`jnl`	Some results on simultaneous stabilization with multiple domains of stability. Autom. M. Vidyasagar
1986	A*	`conf`	Control of a flexible robot arm using the stable factorization approach. ICRA M. Vidyasagar, Y. Xiong
1986	J	`jnl`	Infinite gain margin problem in multivariable feedback systems. Autom. H. Maeda, M. Vidyasagar
1986	J	`jnl`	Robust controllers for uncertain linear multivariable systems. Autom. M. Vidyasagar, H. Kimura
1985	J	`jnl`	Maximal lyapunov functions and domains of attraction for autonomous nonlinear systems. Autom. Anthony Vannelli, M. Vidyasagar
1985	J	`jnl`	Reliable stabilization using a multi-controller configuration. Autom. M. Vidyasagar, N. Viswanadham
1983	J	`jnl`	Algebraic and topological aspects of the regulator problem for lumped linear systems. Autom. Bruce A. Francis, M. Vidyasagar