Submitted/Working Papers
On The Stochastic Follow-the-Regularized Leader in Zero-Sum Games, with James Bailey and Georgios Piliouras. [Arxiv].
Peer Reviewed Conferences
Etienne Bamas, Sai Ganesh Nagarajan, Ola Svensson. Analyzing $D^\alpha$ seeding for $k$-means. [arxiv]. (ICML 2024). (Alphabetical Order)
Marina Drygala, Sai Ganesh Nagarajan, Ola Svensson. Online Algorithms with Costly Predictions. [Paper]. (AISTATS 2023). (Alphabetical Order)
Sai Ganesh Nagarajan, Gerasimos Palaiopanos, Ioannis Panageas, Tushar Vaidya, Samson Yu. Mean estimation of truncated mixtures of two Gaussians: A gradient based approach. [Paper]. (AAAI 2023). (Alphabetical Order)
Arnab Bhattacharyya, Rathin Desai, Sai Ganesh Nagarajan and Ioannis Panageas. Efficient Statistics for Sparse Graphical Models from Truncated Samples. [Arxiv] . (AISTATS 2021). (Alphabetical Order)
Qi Lie, Sai Ganesh Nagarajan, Ioannis Panageas and Xiao Wang. Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes. [Arxiv]. (AISTATS 2021). (Alphabetical Order)
Sai Ganesh Nagarajan, David Balduzzi and Georgios Piliouras. From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics. [Paper] [Code] (ICML 2020).
Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas. Better Depth-Width Trade-offs for Neural Networks through the lens of Dynamical Systems [Paper] [Code]. (ICML 2020). (Alphabetical Order)
Sai Ganesh Nagarajan, David Balduzzi and Georgios Piliouras. Robust Self-organization in Games: Symmetries, Conservation Laws and Dimensionality Reduction [Paper]. (AAMAS 2020, Extended Abstract).
Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas, Xiao Wang. Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem. [Paper] [Code] (ICLR 2020, Spotlight presentation) . (Alphabetical Order)
Sai Ganesh Nagarajan, Ioannis Panageas, On the Analysis of EM for truncated mixtures of two Gaussians. [Arxiv] (ALT 2020) . (Alphabetical Order)
Sai Ganesh Nagarajan, Sameh Mohamed, and Georgios Piliouras. Three body problems in evolutionary game dynamics: Convergence, periodicity and limit cycles. [Paper] (AAMAS 2018).
PhD Thesis
Machine Learning via Dynamical Systems: Applications to Deep Learning, Game Theory and Optimization (2021). [Thesis]
Papers on anomaly detection in sensor networks (Prior PhD)
Gareth W.Peters, Ido Nevat, Sai Ganesh Nagarajan, Tomoko Matsui. Spatial warped Gaussian processes: Estimation and efficient field reconstruction. [Paper]. (Entropy 2021).
Ido Nevat, Dinil Mon Divakaran, Sai Ganesh Nagarajan, Pengfei Zhang, Le Su, Li Ling Ko, and Vrizlynn LL Thing. Anomaly detection and attribution in networks with temporally correlated traffic. IEEE/ACM Transactions on Networking (TON), 26(1):131–144, 2018. [pdf]
Tie Luo, Sai Ganesh Nagarajan. Distributed Anomaly Detection Using Autoencoder Neural Networks in WSN for IoT. ICC 2018. [pdf]
Ido Nevat, Sai Ganesh Nagarajan, Pengfei Zhang. Change Detection of a Subset of High-Dimensional Time Series Data in Sensor Networks. IEEE VTC 2018. [pdf]
Sai Ganesh Nagarajan, Pengfei Zhang, and Ido Nevat. Geo-spatial location estimation for internet of things (IoT) networks with one-way time-of-arrival via stochastic censoring. IEEE Internet of Things Journal, 4(1):205–214, 2017.[pdf]
Pengfei Zhang, Sai Ganesh Nagarajan, and Ido Nevat. Secure location of things (SLoT): Mitigating localization spoofing attacks in the internet of things. IEEE Internet of Things Journal, 4(6):2199–2206, 2017. [pdf]
Wai Hong Ronald Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin C Valera, Hwee-Xian Tan, and Natarajan Gautam. Adaptive duty cycling in sensor networks with energy harvesting using continuous-time markov chain and fluid models. IEEE Journal on Selected Areas in Communications, 33(12):2687–2700, 2015. [pdf]