Roy R. Lederman

26 papers A* 1A 1Misc 2Journal 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Catastrophic Failure of The k-Means Algorithm in High Dimensions, and How Hartigan's Algorithm Avoids It. CoRR Roy R. Lederman, David Silva-Sánchez, Ziling Chen, Gilles Mordant, Amnon Balanov, Tamir Bendory
2025	J	`jnl`	An Observation on Lloyd's k-Means Algorithm in High Dimensions. CoRR David Silva-Sánchez, Roy R. Lederman
2025	J	`jnl`	Multimodal manifold learning using kernel interpolation along geodesic paths. Inf. Fusion Ori Katz, Roy R. Lederman, Ronen Talmon
2023	J	`jnl`	Efficient high-resolution refinement in cryo-EM with stochastic gradient descent. CoRR Bogdan Toader, Marcus A. Brubaker, Roy R. Lederman
2023	J	`jnl`	On Manifold Learning in Plato's Cave: Remarks on Manifold Learning and Physical Phenomena. CoRR Roy R. Lederman, Bogdan Toader
2023	J	`jnl`	Using VAEs to Learn Latent Variables: Observations on Applications in cryo-EM. CoRR Daniel G. Edelberg, Roy R. Lederman
2022	A	`conf`	Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals. AISTATS James A. Brofos, Marylou Gabrié, Marcus A. Brubaker, Roy R. Lederman
2021	A*	`conf`	Evaluating the Implicit Midpoint Integrator for Riemannian Hamiltonian Monte Carlo. ICML James A. Brofos, Roy R. Lederman
2021	J	`jnl`	Manifold Density Estimation via Generalized Dequantization. CoRR James A. Brofos, Marcus A. Brubaker, Roy R. Lederman
2021	J	`jnl`	Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM. CoRR Zhou Fan, Roy R. Lederman, Yi Sun, Tianhao Wang, Sheng Xu
2020	J	`jnl`	Magnetic Manifold Hamiltonian Monte Carlo. CoRR James A. Brofos, Roy R. Lederman
2020	J	`jnl`	Non-Canonical Hamiltonian Monte Carlo. CoRR James A. Brofos, Roy R. Lederman
2020	J	`jnl`	Spectral Flow on the Manifold of SPD Matrices for Multimodal Data Processing. CoRR Ori Katz, Roy R. Lederman, Ronen Talmon
2019	J	`jnl`	Extreme Values of the Fiedler Vector on Trees. CoRR Roy R. Lederman, Stefan Steinerberger
2019	J	`jnl`	Hyper-Molecules: on the Representation and Recovery of Dynamical Structures, with Application to Flexible Macro-Molecular Structures in Cryo-EM. CoRR Roy R. Lederman, Joakim Andén, Amit Singer
2018	Misc	`conf`	Heterogeneous multireference alignment: A single pass approach. CISS Nicolas Boumal, Tamir Bendory, Roy R. Lederman, Amit Singer
2018	J	`jnl`	Learning by coincidence: Siamese networks and common variable learning. Pattern Recognit. Uri Shaham, Roy R. Lederman
2017	J	`jnl`	Continuously heterogeneous hyper-objects in cryo-EM and 3-D movies of many temporal dimensions. CoRR Roy R. Lederman, Amit Singer
2017	J	`jnl`	Heterogeneous multireference alignment: a single pass approach. CoRR Nicolas Boumal, Tamir Bendory, Roy R. Lederman, Amit Singer
2017	J	`jnl`	Numerical Algorithms for the Computation of Generalized Prolate Spheroidal Functions. CoRR Roy R. Lederman
2016	J	`jnl`	A Representation Theory Perspective on Simultaneous Alignment and Classification. CoRR Roy R. Lederman, Amit Singer
2016	J	`jnl`	On the Analytical and Numerical Properties of the Truncated Laplace Transform. Part II. SIAM J. Numer. Anal. Roy R. Lederman, Vladimir Rokhlin
2015	Misc	`conf`	Alternating diffusion for common manifold learning with application to sleep stage assessment. ICASSP Roy R. Lederman, Ronen Talmon, Hau-Tieng Wu, Yu-Lun Lo, Ronald R. Coifman
2015	J	`jnl`	Common Variable Learning and Invariant Representation Learning using Siamese Neural Networks. CoRR Uri Shaham, Roy R. Lederman
2015	J	`jnl`	On the Analytical and Numerical Properties of the Truncated Laplace Transform I. SIAM J. Numer. Anal. Roy R. Lederman, Vladimir Rokhlin
2013	J	`jnl`	A random-permutations-based approach to fast read alignment. BMC Bioinform. Roy R. Lederman