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.
First ABAW 2020 Competition analyzes affective behavior tasks.
Two-stream model recognizes affect from audio and video.
Gold prices show seasonal behavior, with January and July having opposite returns.
Study examines how balancing methods affect model behavior in imbalanced classification problems.
We investigate the trading behavior of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behavior. As endogenous factors we consider returns and volatility, whereas the e…
Neural networks are known to be a class of highly expressive functions able to fit even random input-output mappings with accuracy. In this work, we present properties of neural networks that complement this aspect of expressivity. By using tools from Fourier analysis, we show that deep ReLU networks are biased…
The paper examines how algorithmic classification affects behavior and proposes democratizing stakes to mitigate predatory practices.
Studying the invertibility of deep neural networks (DNNs) provides a principled approach to better understand the behavior of these powerful models. Despite being a promising diagnostic tool, a consistent theory on their invertibility is still lacking. We derive a theoretically motivated approach to explore the preimag…
Human stablecoin transactions predict political risk in cryptocurrency markets.
The paper analyzes how mutable blockchain protocols affect miner behavior and strategic stability.
Sparse Transformers degrade semantic information first, with early layers encoding more.
New framework to test neural network representation similarity measures.
Study finds significant price declines and capital reallocation from centralized to decentralized exchanges after FTX collapse.
The paper shows how data and algorithm interactions affect overparameterized linear regression generalization.
Study examines how classifier performance is affected by training data quality.
Study examines pricing strategies in competitive supply chains with discrete prices.
Automatic understanding of human affect using visual signals is of great importance in everyday human-machine interactions. Appraising human emotional states, behaviors and reactions displayed in real-world settings, can be accomplished using latent continuous dimensions (e.g., the circumplex model of affect). Valence …
Timely detection of Hardware Trojans (HTs) has become a major challenge for secure integrated circuits. We present a run-time methodology for HT detection that employs a multi-parameter statistical traffic modeling of the communication channel in a given System-on-Chip (SoC), named as SIMCom. The main idea is to model …
While market is a social field where information flows over the interacting agents, there have been not so many methods to observe the spreading information in the prices comprising the market. By incorporating the entropy transfer in information theory in its relation to the Granger causality, the paper proposes a tre…
The paper analyzes the non-Gaussian behavior of inflation and unemployment over 70 years using multifractal methods.
In this paper, we provide a unified analysis of temporal difference learning algorithms with linear function approximators by exploiting their connections to Markov jump linear systems (MJLS). We tailor the MJLS theory developed in the control community to characterize the exact behaviors of the first and second order …
The purpose of this paper is to identify the immediate and future retailer response to wholesale stockouts. We perform a statistical analysis of historical customer order and delivery data of a local tool wholesaler and distributor, whose customers are retailers, over a period of four years. We investigate the effect o…
New analysis shows how temporal variability affects online learning performance.
In this paper emphasis is placed on how the behavior of the solutions of a PDE is affected by the geometry of the generalized -quasi-Einstein manifold, and vice versa. Considering a -dimensional generalized -quasi-Einstein manifold which is conformal to a pseudo-Euclidean space, we prove the most general symme…
The paper analyzes numerical instability in variational flows and proposes a diagnostic method.
Social media systems rely on user feedback and rating mechanisms for personalization, ranking, and content filtering. However, when users evaluate content contributed by fellow users (e.g., by liking a post or voting on a comment), these evaluations create complex social feedback effects. This paper investigates how ra…
With the widespread engineering applications ranging from artificial intelligence and big data decision-making, originally a lot of tedious financial data processing, processing and analysis have become more and more convenient and effective. This paper aims to improve the accuracy of stock price forecasting. It improv…
The assessment of co-movement among metals is crucial to better understand the behaviors of the metal prices and the interactions with others that affect the changes in prices. In this study, both Wavelet Analysis and VARMA (Vector Autoregressive Moving Average) models are utilized. First, Multiple Wavelet Coherence (M…
Novel CNN-based gaze scanpath comparison distinguishes experts from novices in dental radiograph interpretation.
In this paper, we analyzed how audio-visual speech enhancement can help to perform the ASR task in a cocktail party scenario. Therefore we considered two simple end-to-end LSTM-based models that perform single-channel audio-visual speech enhancement and phone recognition respectively. Then, we studied how the two model…
Twitter promotes cryptocurrency pump-and-dumps, affecting trading behavior and returns.
We consider the behavior of gradient flow and of discrete and noisy gradient descent. It is commonly noted that the addition of noise to the process of discrete gradient descent can affect the trajectory of gradient descent. In previous work, we observed such effects. There, we considered the case where the minima had …
Advanced ML/DL models predict stock prices using technical analysis.
New model accounts for continuous human trajectories in robotics.
Machine learning is used extensively in recommender systems deployed in products. The decisions made by these systems can influence user beliefs and preferences which in turn affect the feedback the learning system receives - thus creating a feedback loop. This phenomenon can give rise to the so-called "echo chambers" …
Automatic facial behavior analysis has a long history of studies in the intersection of computer vision, physiology and psychology. However it is only recently, with the collection of large-scale datasets and powerful machine learning methods such as deep neural networks, that automatic facial behavior analysis started…
Proposes a framework for balancing fairness and accuracy in data-restricted binary classification.
This study examines how fashion consumption affects self-confidence and buying behavior in Iranian consumers.
Analyzes how learning algorithms affect and are affected by data manipulation.
Commercial banks and other depository institutions in some countries are required to hold in reserve against deposits made by their customers at their Central Bank or Federal Reserve. Although some countries have been eliminated it, this requirement is useful as one of many Central Bank's regulation made to control rat…
The study models life insurance policy cancellations using statistical and machine learning methods.
A major impact of globalization has been the information flow across the financial markets rendering them vulnerable to financial contagion. Research has focused on network analysis techniques to understand the extent and nature of such information flow. It is now an established fact that a stock market crash in one co…
In this work, we investigate whether state-of-the-art object detection systems have equitable predictive performance on pedestrians with different skin tones. This work is motivated by many recent examples of ML and vision systems displaying higher error rates for certain demographic groups than others. We annotate an …
Urban traffic systems worldwide are suffering from severe traffic safety problems. Traffic safety is affected by many complex factors, and heavily related to all drivers' behaviors involved in traffic system. Drivers with aggressive driving behaviors increase the risk of traffic accidents. In order to manage the safety…
Training dynamics reveal neural network complexity.
In this note, we observe the behavior of gradient flow and discrete and noisy gradient descent in some simple settings. It is commonly noted that addition of noise to gradient descent can affect the trajectory of gradient descent. Here, we run some computer experiments for gradient descent on some simple functions, and…
Model detects depression from transcribed interviews using affective language.
Combining global and local explanations improves user understanding of RL agents.