Approximate nearest neighbor (ANN) search is a performance-critical component of many machine learning pipelines. Rigorous benchmarking is essential for evaluating the performance of vector indexes for ANN search. However, the datasets of the existin...
In this paper we show an abundance of complete Kähler metrics with negative holomorphic bisectional curvature on total spaces of certain vector bundles. Assume that such total spaces are endowed with a wider class of nonpositively curved Kähler met...
This study explores a Bayesian algorithmic approach to personalized fragrance recommendation by integrating hierarchical Relevance Vector Machines (RVM) and Jungian personality archetypes. The paper proposes a structured model that links individual s...
We propose a natural language prompt-based retrieval augmented generation (Prompt-RAG), a novel approach to enhance the performance of generative large language models (LLMs) in niche domains. Conventional RAG methods mostly require vector embeddings...
We consider a variant of the classical online linear optimization problem in which at every step, the online player receives a "hint" vector before choosing the action for that round. Rather surprisingly, it was shown that if the hint vector is guara...
We present the first directed searches for long-transient and continuous gravitational waves from ultralight vector boson clouds around known black holes (BHs). We use LIGO data from the first part of the fourth LIGO-Virgo-KAGRA observing run. The se...
In this paper, we introduce `Plücker weight vector' and establish the definition of a weighted Grassmann orbifold $\mbox{Gr}_{\mathbf{b}}(k,n)$, corresponding to a Plücker weight vector `$\mathbf{b}$'. We achieve an explicit classification of weigh...
No-code AI workflow. Drag and drop workflow nodes and use your workflow with your AI agents. (⭐ 942)
The BESS model consists of an effective lagrangian parametrization with dynamical symmetry breaking, describing scalar, vector and axial-vector bound states in a rather general framework. After a brief description of the model and its generalizatio...
This study presents the Cartesian Accumulative Matrix Pipeline (CAMP) architecture, a novel approach designed to enhance matrix multiplication in Vector Architectures (VAs) and Single Instruction Multiple Data (SIMD) units. CAMP improves the processi...
We present a vector-based method to balance chemical reactions. The algorithm builds candidates in a deterministic way, removes duplicates, and always prints coefficients in the lowest whole-number form. For redox cases, electrons and protons/hydroxi...
The study demonstrates the capabilities of a vector-based approach for calculating stoichiometric coefficients in chemical equations, using black powder as an illustrative example. A method is proposed for selecting and constraining intermediate inte...
Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. (⭐ 2157)
We investigate the relation of two fundamental tools in machine learning and signal processing, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resulting optimization problems...
We propose a novel Bayesian heteroskedastic Markov-switching structural vector autoregression with data-driven time-varying identification. The model selects among alternative patterns of exclusion restrictions to identify structural shocks within th...
The LUCIAE model predictions are compared with experimental data on light vector meson ($ρ,ω,φ$) production in pp, p+Pb and Pb+Pb collisions at 158 A GeV. The model reproduces the general trends of the data, but fails in describing the yield of...
Points: 232 | Comments: 138 | Author: nextworddev
A suite of representation learning models for sentence embedding, and some tasks to evaluate them on. (⭐ 83)
every quasi-complete topological vector space is sequentially complete. Cauchy net Complete space Complete topological vector space Quasi-complete space Topological
We initiate the study of multi-attribute group fairness in $k$-nearest neighbor ($k$-NN) search over vector databases. Unlike prior work that optimizes efficiency or query filtering, fairness imposes count constraints to ensure proportional represent...