12 citations · 18 across the 11 of their papers we have counts for
11 papers
Counting Triangles of Graphs via Randomized Trace Estimation with Incomplete Matrix-Vector Products
Soumyadip Ghosh, Lior Horesh, Vasileios Kalantzis +3
Counting triangles in graphs is a fundamental operation in network analysis, underpinning metrics such as clustering coefficients and serving as a signal for community detection, l…
Exact Symmetry as Algebra: Group-Structured Tensors that Enforce Physical Selection Rules
Paulina Hoyos, Shashanka Ubaru, Dongsung Huh +5
Symmetry determines which physical responses of molecules and crystals are allowed and underlies many models used throughout the physical sciences. Yet several widely used machine-…
Stable Iterative Solvers for Ill-conditioned Linear Systems
Vasileios Kalantzis, Mark S. Squillante, Chai Wah Wu
Iterative solvers for large-scale linear systems such as Krylov subspace methods can diverge when the linear system is ill-conditioned, thus significantly reducing the applicabilit…
Multi-Sense Embeddings for Language Models and Knowledge Distillation
Qitong Wang, Mohammed J. Zaki, Georgios Kollias +1
Transformer-based large language models (LLMs) rely on contextual embeddings which generate different (continuous) representations for the same token depending on its surrounding c…
On The Variance of Schatten -Norm Estimation with Gaussian Sketching Matrices
Lior Horesh, Vasileios Kalantzis, Yingdong Lu +1
Monte Carlo matrix trace estimation is a popular randomized technique to estimate the trace of implicitly-defined matrices via averaging quadratic forms across several observations…
On Efficient Solutions of General Structured Markov Processes in Quantum Computational Environments
Vasileios Kalantzis, Mark S. Squillante, Shashanka Ubaru
We study from a theoretical viewpoint the fundamental problem of efficiently computing the stationary distribution of general classes of structured Markov processes. In strong cont…
Stable iterative refinement algorithms for solving linear systems
Chai Wah Wu, Mark S. Squillante, Vasileios Kalantzis +1
Iterative refinement (IR) is a popular scheme for solving a linear system of equations based on gradually improving the accuracy of an initial approximation. Originally developed t…
Topological data analysis on noisy quantum computers
Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson +6
Topological data analysis (TDA) is a powerful technique for extracting complex and valuable shape-related summaries of high-dimensional data. However, the computational demands of…
Directed Graph Auto-Encoders
Georgios Kollias, Vasileios Kalantzis, Tsuyoshi Idé +2
We introduce a new class of auto-encoders for directed graphs, motivated by a direct extension of the Weisfeiler-Leman algorithm to pairs of node labels. The proposed model learns…
PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty
Paz Fink Shustin, Shashanka Ubaru, Małgorzata J. Zimoń +4
Learning data representations under uncertainty is an important task that emerges in numerous scientific computing and data analysis applications. However, uncertainty quantificati…
Solving sparse linear systems with approximate inverse preconditioners on analog devices
Vasileios Kalantzis, Anshul Gupta, Lior Horesh +3
Sparse linear system solvers are computationally expensive kernels that lie at the heart of numerous applications. This paper proposes a flexible preconditioning framework to subst…