3,764 results for Feedback | ESPNcricinfo.com Vector

arxiv.org/abs/1705.07437v1

Powerful sets: a generalisation of binary matroids

A set $S\subseteq\{0,1\}^E$ of binary vectors, with positions indexed by $E$, is said to be a \textit{powerful code} if, for all $X\subseteq E$, the number of vectors in $S$ that are zero in the positions indexed by $X$ is a power of 2. By treating b...

arxiv.org/abs/2505.17810v1

VIBE: Vector Index Benchmark for Embeddings

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...

arxiv.org/abs/2002.04726v2

Online Learning with Imperfect Hints

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...

arxiv.org/abs/2411.01944v2

KPCA for Thrust Vectoring Systems Exhibiting Singular Points

This paper considers a class of thrust vectoring systems, which are nonlinear, overactuated, and time-invariant. We assume that the system is composed of two subsystems and there exist singular points around which the linearized system is uncontrolla...

github.com/AndersonBY/vector-vein

AndersonBY/vector-vein

No-code AI workflow. Drag and drop workflow nodes and use your workflow with your AI agents. (⭐ 942)

arxiv.org/abs/hep-ph/9411291v1

The Bess Model at Future Colliders

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...

github.com/tensorchord/pgvecto.rs

tensorchord/pgvecto.rs

Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. (⭐ 2157)

arxiv.org/abs/1303.1152v2

An Equivalence between the Lasso and Support Vector Machines

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...

arxiv.org/abs/2502.19659v1

Time-Varying Identification of Structural Vector Autoregressions

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...