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arXiv research

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.

168,742 papers · 148 categories

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1234 · Oct 201919922001200920172026
26 results for happiness

Study finds 'happiness' search data predicts stock returns, suggesting utility needs impact firm performance.

problem Investing in firms that meet societal utility needs.
method Used Google Trends data on 'happiness' search volume to predict stock returns.
result Happiness search exposure (HSE) explains future stock returns, particularly for big and value firms.

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…

2018-06-27abs ↗pdf ↗

Let Πbe a link projection in S^2. John Conway and later Francis Bonahon and Larry Siebenmann undertook to split ΠΠ 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…

2009-06-11abs ↗pdf ↗

The main idea of this ISO is to use StarGAN (A type of GAN model) to perform training and testing on an emotion dataset resulting in a emotion recognition which can be generated by the valence arousal score of the 7 basic expressions. We have created an entirely new dataset consisting of 4K videos. This dataset consist…

2019-10-12abs ↗pdf ↗

Generates diverse images by resampling specific parts while maintaining global consistency.

problem Creating diverse images while maintaining global consistency in certain parts.
method Developed a new network architecture, training procedure, and resampling algorithm.
result Achieved low distortion block-resampling with spatially stochastic networks.

This study examines how market makers balance risk and impact in foreign exchange markets.

problem Balancing risk management with market impact in foreign exchange markets.
method An intermediate scenario approach considering both instantaneous and permanent market impact components.
result Transient market impact is more prevalent than previously thought, challenging traditional market impact models.

New optimization method for portfolio management maximizing wealth and utility with risk control.

problem Maximizing terminal wealth and utility with mean-variance risk control.
method Transformed into a single-objective problem using overall happiness, solved in game theoretic framework.
result Closed-form solutions for specific utility functions reveal new optimal investment strategies.

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…

2017-09-17abs ↗pdf ↗

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…

2018-02-05abs ↗pdf ↗

New framework constructs holographic tensor networks using hyperbolic buildings.

problem Building holographic tensor networks for non-integer dimensions and fractal spaces.
method Introducing a unifying framework based on hyperbolic buildings and dualities.
result Constructs a family of bulk regions satisfying complementary recovery and Ryu-Takayanagi formula.

Mitigates bias in text classification by weighting instances.

problem Unintended biases in text classification datasets based on demographic terms.
method Instance weighting to recover non-discrimination distribution.
result Effective mitigation of unintended biases without sacrificing generalization.

End-to-end deep learning detects emotions in real-life emergency calls.

problem Recognizing emotions in real-life emergency call center recordings.
method Used an end-to-end deep learning architecture trained on IEMOCAP and CEMO datasets.
result Obtained 45.6% Unweighted Accuracy Recall on CEMO with 4 classes, 76.9% on 2 classes (Anger, Neutral).