A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper explores using hand gestures to type English letters.
FineHand learns hand shapes for better ASL recognition.
Classifying limb movements using brain activity is an important task in Brain-computer Interfaces (BCI) that has been successfully used in multiple application domains, ranging from human-computer interaction to medical and biomedical applications. This paper proposes a novel solution for classification of left/right h…
By adopting the polynomial interpolation method, we propose an approach to hedge against the interest-rate risk of the default-free bonds by measuring the nonparallel movement of the yield-curve, such as the translation, the rotation and the twist. The empirical analysis shows that our hedging strategies are comparable…
An internal model of the own body can be assumed a fundamental and evolutionary-early representation as it is present throughout the animal kingdom. Such functional models are, on the one hand, required in motor control, for example solving the inverse kinematic or dynamic task in goal-directed movements or a forward t…
Developed Taylor series for muscle-finger system analysis.
In this article we discuss the distribution of asset price movements by the market potential function. From the principle of free energy minimization we analyze two different kinds of market potentials. We obtain a U-shaped potential when market reversion (i.e. contrarian investors) is dominant. On the other hand, if t…
Transformer models predict financial time series movements accurately.
Paper uses deep Q-network to correct eye movement artifacts in OCT volumes.
Study shows integrating OFI from multiple levels improves price impact explanation but not forecasting.
In this article we review several techniques to extract information from stock market data. We discuss recurrence analysis of time series, decomposition of aggregate correlation matrices to study co-movements in financial data, stock level partial correlations with market indices, multidimensional scaling and minimum s…
Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical and quantitative analysis and tested their validity on short-term mid-price movement prediction. We f…
Designing of touchless user interface is gaining popularity in various contexts. Using such interfaces, users can interact with electronic devices even when the hands are dirty or non-conductive. Also, user with partial physical disability can interact with electronic devices using such systems. Research in this direct…
Framework uses optimal transport for neural architecture search.
The growing use of virtual autonomous agents in applications like games and entertainment demands better control policies for natural-looking movements and actions. Unlike the conventional approach of hard-coding motion routines, we propose a deep learning method for obtaining control policies by directly mimicking raw…
Paper reduces movement primitive dimensionality in parameter space.
Algorithm optimizes lockdown policies balancing health and economy.
Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for…
We recast the Calabi flow in DeGiorgi's language of minimizing movements. We establish the long time existence of minimizing movements for K-energy with arbitrary initial condition. Furthermore we establish some a priori regularity of these solutions, and that sufficiently regular minimizing movements are smooth soluti…
Most policy search algorithms require thousands of training episodes to find an effective policy, which is often infeasible with a physical robot. This survey article focuses on the extreme other end of the spectrum: how can a robot adapt with only a handful of trials (a dozen) and a few minutes? By analogy with the wo…
Taureau uses Twitter sentiment analysis to predict stock market movement.
Study forecasts Bitcoin prices using ML algorithms.
Neural nets predict user attention from mouse movements.
Paper proves minimizing movements match smooth droplet flow in 3D.
MPANF improves naive forecast by incorporating directional information.
We study involuntary micro-movements of the eye for biometric identification. While prior studies extract lower-frequency macro-movements from the output of video-based eye-tracking systems and engineer explicit features of these macro-movements, we develop a deep convolutional architecture that processes the raw eye-t…
New sEMG dataset for ADL activities recognized with high accuracy.
Neuroscientific studies of drawing-like movements usually analyze neural representation of either geometric (eg. direction, shape) or temporal (eg. speed) features of trajectories rather than trajectory's representation as a whole. This work is about empirically supported mathematical ideas behind splitting and merging…
Study identifies key trades predicting market movements.
The study introduces a new stickiness parameter for stock prices using a non-linear model.
The rise of non-linear and interactive media such as video games has increased the need for automatic movement animation generation. In this survey, we review and analyze different aspects of building automatic movement generation systems using machine learning techniques and motion capture data. We cover topics such a…
Bayesian method infers local rules for collective animal movement.
Optimizing data movement significantly improves transformer training efficiency.
NoTMF forecasts sparse urban road movement speeds with nonstationary temporal matrix factorization.
Study on pseudo-Riemannian Bertrand manifolds finds no closed movement systems.
Study identifies personality traits from dance movements in music.
We propose channel charting (CC), a novel framework in which a multi-antenna network element learns a chart of the radio geometry in its surrounding area. The channel chart captures the local spatial geometry of the area so that points that are close in space will also be close in the channel chart and vice versa. CC w…
Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of …
New algorithm reduces dynamic regret in time-varying movement costs.
Generically learns movement control policies from exploration data.
Study on droplet flow on uneven surfaces, proving existence and properties.
Framework analyzes stock price co-movement with fundamentals using big data.
Alternative proof of weak solutions to mean curvature flow using minimizing movements.
Wrist movements can reveal digits, posing security risks.
Deep learning predicts VR head movements for better 360-degree videos.
The paper presents a step forward into the development of the theory of meaning. Stock and financial markets are examined from communication-theoretical perspective on the dynamics of information and meaning. This study focuses on the link between the dynamics of investors' expectations and market price movement. The m…
Enhances stock movement prediction using Higher Order Transformers for multimodal time-series data.
This paper predicts weekly stock market movements using machine learning and introduces a new benchmark.