Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity

arXiv:2606.27298 · cs.DS, cs.LG, math.ST, stat.ML · Submitted 2026-06-25 · Read on arXiv

Haitong Liu, Deepak Narayanan Sridharan, David Steurer, Manuel Wiedmer

cs.DS, cs.LG, math.ST, stat.ML

Submitted: 2026-06-25

Comments: 88 pages; accepted at the 39th Annual Conference on Learning Theory (COLT 2026)

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Sample Complexity — 53× in this paper · explained in 20 episodes
Preconditioning — 18× in this paper · explained in 2 episodes
Accuracy — 9× in this paper · explained in 1 episode
Robustness — 8× in this paper · explained in 6 episodes
Method of Moments — 6× in this paper
Annual Symposium on Foundations of Computer Science — 3× in this paper
Annual ACM-SIAM Symposium on Discrete Algorithms — 2× in this paper
Clustering — 2× in this paper · explained in 2 episodes
Monotonicity — 2× in this paper · explained in 2 episodes
Nuclear Norm — 2× in this paper · explained in 2 episodes
Preconditioner — 2× in this paper · explained in 2 episodes
Differentially Private — 1× in this paper · explained in 3 episodes
Orthogonal Projection — 1× in this paper · explained in 2 episodes
Papers — 1× in this paper · explained in 3 episodes
Total Variation (TV) distance — 1× in this paper · explained in 2 episodes
Trace — 1× in this paper · explained in 2 episodes

Related papers