www.reddit.com/r/vectorart/comments/kl82r2/this_time_i_will_pass_the_hifi_sunday_a_bit_and/
This time I will pass the Hi-Fi Sunday a bit and bring a work asked to me some w…
...
en.wikipedia.org/wiki/Multi-objective_optimization
Multi-objective optimization - Wikipedia
Multi-objective optimization or Pareto optimization (also known as multi-objective programming, vector optimization, multicriteria optimization, or multiattribute
arxiv.org/abs/1601.03295v1
Document image classification, with a specific view on applications of patent im…
The main focus of this paper is document image classification and retrieval, where we analyze and compare different parameters for the RunLeght Histogram (RL) and Fisher Vector (FV) based image representations. We do an exhaustive experimental study...
arxiv.org/abs/2207.11497v1
Patent Search Using Triplet Networks Based Fine-Tuned SciBERT
In this paper, we propose a novel method for the prior-art search task. We fine-tune SciBERT transformer model using Triplet Network approach, allowing us to represent each patent with a fixed-size vector. This also enables us to conduct efficient ve...
arxiv.org/abs/2011.11744v1
The Bloom Clock for Causality Testing
Testing for causality between events in distributed executions is a fundamental problem. Vector clocks solve this problem but do not scale well. The probabilistic Bloom clock can determine causality between events with lower space, time, and message-...
arxiv.org/abs/1905.13064v4
The Bloom Clock
The bloom clock is a space-efficient, probabilistic data structure designed to determine the partial order of events in highly distributed systems. The bloom clock, like the vector clock, can autonomously detect causality violations by comparing its...
arxiv.org/abs/0802.2249v1
Towards a Real-time Transient Classification Engine
Temporal sampling does more than add another axis to the vector of observables. Instead, under the recognition that how objects change (and move) in time speaks directly to the physics underlying astronomical phenomena, next-generation wide-field s...
arxiv.org/abs/2006.10299v3
A quantum extension of SVM-perf for training nonlinear SVMs in almost linear tim…
We propose a quantum algorithm for training nonlinear support vector machines (SVM) for feature space learning where classical input data is encoded in the amplitudes of quantum states. Based on the classical SVM-perf algorithm of Joachims, our algor...
arxiv.org/abs/1004.0240v2
B-meson decays to eta' rho, eta' f0, and eta' K*
We present measurements of B-meson decays to the final states eta'rho, eta'f0, and eta'K*, where K* stands for a vector, scalar, or tensor strange meson. We observe a significant signal or evidence for eta'rho+ and all the eta'K* channels. We also me...
arxiv.org/abs/1605.00347v1
Parameter estimation for linear control valve with hysteresis
The problem of estimating parameters of linear control valve with hysteresis is considered. The hysteretic behavior of control valve is formulated as a switched linear model. An indicator vector, which shows the switching epochs of switched linear mo...
arxiv.org/abs/2507.12638v1
Reasoning-Finetuning Repurposes Latent Representations in Base Models
Backtracking, an emergent behavior elicited by reasoning fine-tuning, has been shown to be a key mechanism in reasoning models' enhanced capabilities. Prior work has succeeded in manipulating this behavior via steering vectors, but the underlying mec...
arxiv.org/abs/2209.06880v1
Vector Time Series Modelling of Turbidity in Dublin Bay
Turbidity is commonly monitored as an important water quality index. Human activities, such as dredging and dumping operations, can disrupt turbidity levels and should be monitored and analyzed for possible effects. In this paper, we model the variat...
en.wikipedia.org/wiki/Gauss%E2%80%93Markov_theorem
Gauss–Markov theorem - Wikipedia
variance of the linear combination.) The best linear unbiased estimator (BLUE) of the vector β {\displaystyle \beta } of parameters β j {\displaystyle
arxiv.org/abs/1705.07806v1
A unified approach to the design and analysis of AMG
In this work, we present a general framework for the design and analysis of two-level AMG methods. The approach is to find a basis for locally optimal or quasi-optimal coarse space, such as the space of constant vectors for standard discretizations o...
arxiv.org/abs/1907.04417v1
Improving Solve Time of aggregation-based adaptive AMG
This paper proposes improving the solve time of a bootstrap AMG designed previously by the authors. This is achieved by incorporating the information, set of algebraically smooth vectors, generated by the bootstrap algorithm, in a single hierarchy by...
arxiv.org/abs/1504.07638v2
Bottom and Charm Mass Determinations with a Convergence Test
We present new determinations of the MS-bar charm quark mass using relativistic QCD sum rules at O(alpha_s^3) from the moments of the vector and the pseudoscalar current correlators. We use available experimental measurements from e+e- collisions and...
arxiv.org/abs/1709.02261v3
Extracting data from vector figures in scholarly articles
It is common for authors to communicate their results in graphical figures, but those data are frequently unavailable for reanalysis. Reconstructing data points from a figure manually requires the author to measure the coordinates either on printed p...
arxiv.org/abs/2209.04460v1
Figure and Figure Caption Extraction for Mixed Raster and Vector PDFs: Digitizat…
Scientific articles published prior to the "age of digitization" in the late 1990s contain figures which are "trapped" within their scanned pages. While progress to extract figures and their captions has been made, there is currently no robust method...
arxiv.org/abs/2101.03029v2
"Let's Eat Grandma": Does Punctuation Matter in Sentence Representation?
Neural network-based embeddings have been the mainstream approach for creating a vector representation of the text to capture lexical and semantic similarities and dissimilarities. In general, existing encoding methods dismiss the punctuation as insi...
arxiv.org/abs/2405.20822v1
Inflation Determinants in Argentina (2004-2022)
This paper analyzes the empirical relationship between the inflation rate and its proximate determinants in Argentina, using quarterly data over the period 2004-2022 and an error-correction vector model approach. Unlike previous literature, this pape...