My primary research agenda lies at the intersection of machine learning, risk estimation, and information processing. Specifically, my work focuses on two complementary and interacting research directions: (1) robust, scalable, and adaptive machine learning methodologies for high-dimensional data and (2) how information processing with computational constraints shapes learning in biological and artificial systems.
Full Publication List
Manuscripts:
A. Auddy, H. Zou, K. Rahnama Rad, and A. Maleki. "Approximate Leave-one-out Cross Validation for Regression with 𝑙1 Regularizers." Under review: IEEE Transactions of Information Theory.
H. Zou, A. Auddy, K. Rahnama Rad, and A. Maleki. Fast Scalable Out-of-sample Risk Estimation for Trend Filtering on Graphs, work in progress.
H. Zou, A. Auddy, K. Rahnama Rad, and A. Maleki. Theoretical Analysis of n-fold Cross Validation for Non-differentiable Penalties under High-dimensional settings, submitted to ICML 2024.
K. Rahnama Rad, Y. Yue, and A. Mejia. "Scalable and Fully Bayesian Trend Filtering on Large Graphs." Under review: The Journal of Machine Learning Research.
Published journal articles:
K. Florez, N. Hwang, S. Verdaguer-Johe, M. Hernadez, and K. Rahnama Rad. "A mixed method exploration of individual and network-level factors and Type 2 Diabetes Mellitus (T2DM) among Mexican American adults in New York City." Plos one, 19(1), e0295499.
J. Xu, A. Maleki, K. Rahnama Rad, and D. Hsu. "Consistent Risk Estimation in High-Dimensional Linear Regression." IEEE Transactions on Information Theory 67, no. 9 (2021): 5997-6030.
K. Rahnama Rad and A. Maleki. "A scalable estimate of the out-of-sample prediction error via approximate leave-one-out." Journal of the Royal Statistical Society: Series B 84, no. 2 (2020): 965-996.
K. Rahnama Rad, T. Machado, and L. Paninski. "Robust and scalable Bayesian analysis of spatial neural tuning function data." Annals of Applied Statistics 11, no. 2 (2017): 598-637.
E. Pnevmatikakis, K. Rahnama Rad, J. Huggins, and L. Paninski. "Fast Kalman filtering and forward-backward smoothing via a low-rank perturbative approach." Journal of Computational and Graphical Statistics 23, no. 2 (2014): 316-339.
P. Molavi, A. Jadbabaie, K. Rahnama Rad, and A. Tahbaz-Salehi. "Reaching Consensus with increasing information." IEEE Journal of Selected Topics in Signal Processing 7, no. 2 (2013): 358-370.
K. Rahnama Rad. "Nearly sharp sufficient conditions on exact sparsity pattern recovery." IEEE Transactions Information Theory 57, no. 7 (2011): 4672-4679.
K. Rahnama Rad and L. Paninski. "Efficient estimation of two-dimensional firing rate surfaces via gaussian process methods." Network: Computation in Neural Systems 21, (2010): 142-168.
L. Paninski, Y. Ahmadian, D. Ferreira, S. Koyama, K. Rahnama Rad, M. Vidne, J. Vogelstein, and W. Wu. "A new look at state-space models for neural data." Journal of Computational Neuroscience 29, (2009): 107-126.
T. Toyoizumi, K. Rahnama Rad, and L. Paninski. "Mean-field approximations for coupled populations of generalized linear model spiking neurons with Markov refractoriness." Neural Computation 21, (2009): 1203-1243.
K. Rahnama Rad and M. Nasiri-Kenari. "Iterative detection for V-BLAST MIMO communication systems based on expectation maximisation algorithm." IEE Electronics Letters 40, no. 11 (2004): 684-685.
Refereed conference publications:
A. Auddy, H. Zou, K. Rahnama Rad, and A. Maleki. "Approximate Leave-one-out Cross Validation for Regression with l1 Regularizers." accepted International Conference on Artificial Intelligence and Statistics (2024).
K. Rahnama Rad, W. Zhou, and A. Maleki. "Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions." International Conference on Artificial Intelligence and Statistics (2020): 4067-4077.
P. Molavi, K. Rahnama Rad, A. Tahbaz-Salehi, and A. Jadbabaie. "On consensus and exponentially fast social learning." IEEE American Control Conference (2012): 2165-2170.
L. Paninski, K. Rahnama Rad, and M. Vidne. "Robust particle filters via sequential pairwise reparameterized Gibbs sampling." Conference on Information Sciences and Systems (2012): 1-6.
K. Rahnama Rad and L. Paninski. "Information rates and optimal decoding in large neural populations." Advances in Neural Information Processing Systems (2011): 846-854.
K. Rahnama Rad and A. Tahbaz-Salehi. "Distributed parameter estimation in networks." IEEE Conference on Decision and Control (2010): 5050-5055.
K. Rahnama Rad. "Sharp upper bound on error probability of exact sparsity recovery." IEEE Conference on Information Sciences and Systems (2009): 14-17.
K. Rahnama Rad and M. Nasiri-Kenari. "Expectation maximization based detection for VBLAST MIMO communication systems and performance evaluation." IEEE International Symposium on Spread Spectrum Techniques and Applications (2004): 255-259.