Approximate Leave-One-Out Cross Validation for Regression With ℓ₁ Regularizers.
IEEE Trans. Inf. Theory, November, 2024
Approximate Leave-one-out Cross Validation for Regression with ℓ<sub>1</sub> Regularizers.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
Consistent Risk Estimation in Moderately High-Dimensional Linear Regression.
IEEE Trans. Inf. Theory, 2021
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
Consistent Risk Estimation in High-Dimensional Linear Regression.
CoRR, 2019
Reaching Consensus With Increasing Information.
IEEE J. Sel. Top. Signal Process., 2013
Robust particle filters via sequential pairwise reparameterized Gibbs sampling.
Proceedings of the 46th Annual Conference on Information Sciences and Systems, 2012
On consensus and exponentially fast social learning.
Proceedings of the American Control Conference, 2012
Nearly Sharp Sufficient Conditions on Exact Sparsity Pattern Recovery.
IEEE Trans. Inf. Theory, 2011
Information Rates and Optimal Decoding in Large Neural Populations.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011
A new look at state-space models for neural data.
J. Comput. Neurosci., 2010
Distributed parameter estimation in networks.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010
Mean-Field Approximations for Coupled Populations of Generalized Linear Model Spiking Neurons with Markov Refractoriness.
Neural Comput., 2009
Sharp Sufficient Conditions on Exact Sparsity Pattern Recovery
CoRR, 2009
Sharp upper bound on error probability of exact sparsity recovery.
Proceedings of the 43rd Annual Conference on Information Sciences and Systems, 2009