355 citations · 730 across the 16 of their papers we have counts for
17 papers
Beyond Effective Sample Size: Effective Number of Proposals for Adaptive Importance Sampling
Ali Mousavi, Victor Elvira
Population-based adaptive importance sampling (AIS) methods use a set of proposal densities to approximate complex target distributions. Their performance is commonly assessed thro…
Balanced Adaptive Prototype Selection for Scalable TabPFN Inference on Large-Scale Tabular Data
Mahboobe Jadid, Melika Rezaye Garkani, Ali Mousavi
Pretrained tabular foundation models have demonstrated strong predictive capability; however, their application to large-scale datasets remains constrained by the limited inference…
Growing and Serving Large Open-domain Knowledge Graphs
Ihab F. Ilyas, JP Lacerda, Yunyao Li +5
Applications of large open-domain knowledge graphs (KGs) to real-world problems pose many unique challenges. In this paper, we present extensions to Saga our platform for continuou…
High-Throughput Vector Similarity Search in Knowledge Graphs
Jason Mohoney, Anil Pacaci, Shihabur Rahman Chowdhury +5
There is an increasing adoption of machine learning for encoding data into vectors to serve online recommendation and search use cases. As a result, recent data management systems…
Hamiltonian Adaptive Importance Sampling
Ali Mousavi, Reza Monsefi, Víctor Elvira
Importance sampling (IS) is a powerful Monte Carlo (MC) methodology for approximating integrals, for instance in the context of Bayesian inference. In IS, the samples are simulated…
Adaptive Neuro Fuzzy Networks based on Quantum Subtractive Clustering
Ali Mousavi, Mehrdad Jalali, Mahdi Yaghoubi
Data mining techniques can be used to discover useful patterns by exploring and analyzing data and it's feasible to synergitically combine machine learning tools to discover fuzzy…