Kamiar Rahnama Rad

发表

Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions

Arian Maleki, Kamiar Rahnama Rad, Wenda Zhou, 2020, AISTATS.

Mean-Field Approximations for Coupled Populations of Generalized Linear Model Spiking Neurons with Markov Refractoriness

Kamiar Rahnama Rad, Liam Paninski, Taro Toyoizumi, 2009, Neural Computation.

Consistent Risk Estimation in High-Dimensional Linear Regression pdf

Arian Maleki, Ji Xu, Kamiar Rahnama Rad, 2019, ArXiv.

Robust particle filters via sequential pairwise reparameterized Gibbs sampling

Kamiar Rahnama Rad, Liam Paninski, Michael Vidne, 2012, 2012 46th Annual Conference on Information Sciences and Systems (CISS).

Reaching Consensus With Increasing Information

Kamiar Rahnama Rad, Pooya Molavi, Alireza Tahbaz-Salehi, 2013, IEEE Journal of Selected Topics in Signal Processing.

A new look at state-space models for neural data

Wei Wu, Joshua T. Vogelstein, Kamiar Rahnama Rad, 2010, Journal of Computational Neuroscience.

Nearly Sharp Sufficient Conditions on Exact Sparsity Pattern Recovery

Kamiar Rahnama Rad, 2009, IEEE Transactions on Information Theory.

Robust and scalable Bayesian analysis of spatial neural tuning function data

Kamiar Rahnama Rad, Liam Paninski, Timothy A. Machado, 2016, 1606.07845.

Sharp upper bound on error probability of exact sparsity recovery

Kamiar Rahnama Rad, 2009, 2009 43rd Annual Conference on Information Sciences and Systems.

Distributed parameter estimation in networks

Kamiar Rahnama Rad, Alireza Tahbaz-Salehi, A. Tahbaz-Salehi, 2010, 49th IEEE Conference on Decision and Control (CDC).

Information Rates and Optimal Decoding in Large Neural Populations

Kamiar Rahnama Rad, Liam Paninski, L. Paninski, 2011, NIPS.

Consistent Risk Estimation in Moderately High-Dimensional Linear Regression

Arian Maleki, Ji Xu, Kamiar Rahnama Rad, 2019 .

Consistent Risk Estimation in Moderately High-Dimensional Linear Regression

Arian Maleki, Kamiar Rahnama Rad, Daniel Hsu, 2021, IEEE Transactions on Information Theory.

A scalable estimate of the extra-sample prediction error via approximate leave-one-out

Kamiar Rahnama Rad, A. Maleki, 2018, 1801.10243.

Sparse superposition codes for Gaussian vector quantization

Kamiar Rahnama Rad, Ioannis Kontoyiannis, S. Gitzenis, 2010, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo).

Efficient, adaptive estimation of two-dimensional firing rate surfaces via Gaussian process methods

Kamiar Rahnama Rad, L. Paninski, 2010, Network.

Fast Kalman Filtering and Forward–Backward Smoothing via a Low-Rank Perturbative Approach

Kamiar Rahnama Rad, L. Paninski, Jonathan Huggins, 2014 .

Fast Kalman filtering via a low-rank perturbative approach

Kamiar Rahnama Rad, L. Paninski, Jonathan Huggins, 2011 .

A scalable estimate of the out‐of‐sample prediction error via approximate leave‐one‐out cross‐validation

Arian Maleki, Kamiar Rahnama Rad, A. Maleki, 2020, Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Consistent Risk Estimation in Moderately High-Dimensional Linear Regression

Kamiar Rahnama Rad, Daniel J. Hsu, A. Maleki, 2019, IEEE Transactions on Information Theory.

High dimensional Information Processing

Kamiar Rahnama Rad, Kamiar Rahnama Rad, 2011 .

On consensus and exponentially fast social learning

Ali Jadbabaie, Kamiar Rahnama Rad, Pooya Molavi, 2012, 2012 American Control Conference (ACC).

Mean-Field Approximations for Coupled Populations of Generalized Linear Model Spiking Neurons with Markov Refractoriness

Kamiar Rahnama Rad, L. Paninski, T. Toyoizumi, 2009, Neural Computation.

Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings

Kamiar Rahnama Rad, A. Maleki, Arnab Auddy, 2024, 2402.08543.

A scalable estimate of the extra-sample prediction error via approximate leave-one-out

Kamiar Rahnama Rad, A. Maleki, 2018, 1801.10243.