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.
The paper proposes a happiness-based fairness framework using linear programming.
Study finds 'happiness' search data predicts stock returns, suggesting utility needs impact firm performance.
Task offloading is an emerging technology in fog-enabled networks. It allows users to transmit tasks to neighbor fog nodes so as to utilize the computing resources of the networks. In this paper, we investigate a stochastic task offloading model and propose a multi-armed bandit framework to formulate this model. We con…
AI misidentifies facial expressions in videos, often misinterpreting happiness as sadness.
This research improves emotion detection from speech, enhancing CCC by 30%.
Let Πbe a link projection in S^2. John Conway and later Francis Bonahon and Larry Siebenmann undertook to split into canonical pieces. These pieces received different names: basic or polyhedral diagrams on one hand, rational, algebraic, bretzel, arborescent diagrams on the other hand. This paper proposes a thorough…
The web is loaded with textual content, and Natural Language Processing is a standout amongst the most vital fields in Machine Learning. But when data is huge simple Machine Learning algorithms are not able to handle it and that is when Deep Learning comes into play which based on Neural Networks. However since neural …
What predicts the evolution over time of subjective well-being? We correlate the trends of subjective well-being with the trends of social capital and/or GDP. We find that in the long and medium run social capital largely predicts the trends of subjective wellbeing in our sample of countries. In the short-term this rel…
Generates diverse images by resampling specific parts while maintaining global consistency.
This study examines how market makers balance risk and impact in foreign exchange markets.
New optimization method for portfolio management maximizing wealth and utility with risk control.
StarGAN model generates and recognizes emotions from facial expressions.
This paper focuses on the problem of explaining predictions of psychological attributes such as attractiveness, happiness, confidence and intelligence from face photographs using deep neural networks. Since psychological attribute datasets typically suffer from small sample sizes, we apply transfer learning with two ba…
Transformer learns long-term dependencies from real-world data.
Tactile enhanced multimedia is generated by synchronizing traditional multimedia clips, to generate hot and cold air effect, with an electric heater and a fan. This objective is to give viewers a more realistic and immersing feel of the multimedia content. The response to this enhanced multimedia content (mulsemedia) i…
Recently, digital music libraries have been developed and can be plainly accessed. Latest research showed that current organization and retrieval of music tracks based on album information are inefficient. Moreover, they demonstrated that people use emotion tags for music tracks in order to search and retrieve them. In…
This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks. We assume no math knowledge beyond what you learned in calculus 1, and provide links to help you refresh the necessary math where needed. Note that you do not need to understand this materia…
New framework constructs holographic tensor networks using hyperbolic buildings.
Mitigates bias in text classification by weighting instances.
New algorithms for fair item allocation with limited copies.
In this paper, we design an integrated algorithm to evaluate the sentiment of Chinese market. Firstly, with the help of the web browser automation, we crawl a lot of news and comments from several influential financial websites automatically. Secondly, we use techniques of Natural Language Processing(NLP) under Chinese…
Objective. The paper investigates the presence of autism using the functional brain connectivity measures derived from electro-encephalogram (EEG) of children during face perception tasks. Approach. Phase synchronized patterns from 128-channel EEG signals are obtained for typical children and children with autism spect…
Convolutional neural networks (CNN) are widely used for speech emotion recognition (SER). In such cases, the short time fourier transform (STFT) spectrogram is the most popular choice for representing speech, which is fed as input to the CNN. However, the uncertainty principles of the short-time Fourier transform preve…
End-to-end deep learning detects emotions in real-life emergency calls.
Unified facial behavior analysis network improves performance across tasks.
Study predicts Type 2 diabetes with 85% accuracy using machine learning.