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.
Study proposes an ad creative selection algorithm considering user fatigue.
Adaptive algorithm for online evaluation of targeted audiences in advertising.
Much work has been done in understanding human creativity and defining measures to evaluate creativity. This is necessary mainly for the reason of having an objective and automatic way of quantifying creative artifacts. In this work, we propose a regression-based learning framework which takes into account quantitative…
Paper proposes using creative ML for game design.
Deep learning model for AI co-creativity boosts design creativity.
The common view that our creativity is what makes us uniquely human suggests that incorporating research on human creativity into generative deep learning techniques might be a fruitful avenue for making their outputs more compelling and human-like. Using an original synthesis of Deep Dream-based convolutional neural n…
Paper proposes a new ML framework to enhance creativity in music generation.
We present a system for identifying conceptual shifts between visual categories, which will form the basis for a co-creative drawing system to help users draw more creative sketches. The system recognizes human sketches and matches them to structurally similar sketches from categories to which they do not belong. This …
Paper explores how generative models can be made more creative.
Theory explains creativity in diffusion models generating novel images.
Top-H decoding improves text generation by balancing creativity and coherence.
Robots learn to handle complex tasks creatively using DRL.
A new method for generating realistic and creative 3D shapes from point clouds.
AI generates sculptural objects through machine learning.
In markets for online advertising, some advertisers pay only when users respond to ads. So publishers estimate ad response rates and multiply by advertiser bids to estimate expected revenue for showing ads. Since these estimates may be inaccurate, the publisher risks not selecting the ad for each ad call that would max…
We show that world trade network datasets contain empirical evidence that the dynamics of innovation in the world economy follows indeed the concept of creative destruction, as proposed by J.A. Schumpeter more than half a century ago. National economies can be viewed as complex, evolving systems, driven by a stream of …
Machine learning models predict which ideas will be innovated based on subjective perspectives.
Study copyright's impact on creative industries using AI-generated fonts.
Comparison Lift uses bandit algorithms to optimize online ad testing.
On most sponsored search platforms, advertisers bid on some keywords for their advertisements (ads). Given a search request, ad retrieval module rewrites the query into bidding keywords, and uses these keywords as keys to select Top N ads through inverted indexes. In this way, an ad will not be retrieved even if querie…
Abstraction and realization are bilateral processes that are key in deriving intelligence and creativity. In many domains, the two processes are approached through rules: high-level principles that reveal invariances within similar yet diverse examples. Under a probabilistic setting for discrete input spaces, we focus …
Diffusion models improve creativity by smoothing the score function, leading to interpolated data.
New method quantifies deep kNN anomaly detection significance.
Genome-wide association studies (GWAS) have achieved great success in the genetic study of Alzheimer's disease (AD). Collaborative imaging genetics studies across different research institutions show the effectiveness of detecting genetic risk factors. However, the high dimensionality of GWAS data poses significant cha…
A deep learning approach generates math word problems in multiple languages.
Can an algorithm create original and compelling fashion designs to serve as an inspirational assistant? To help answer this question, we design and investigate different image generation models associated with different loss functions to boost creativity in fashion generation. The dimensions of our explorations include…
One of the defining characteristics of human creativity is the ability to make conceptual leaps, creating something surprising from typical knowledge. In comparison, deep neural networks often struggle to handle cases outside of their training data, which is especially problematic for problems with limited training dat…
SI-CLAD improves clustering-based anomaly detection by controlling false positives.
Proposes a statistical test for VAE-based anomaly detection reliability.
AI enhances financial services but humans are irreplaceable for empathy, presence, and ethics.
We discuss classical gravitational aspects of the AdS/CFT correspondence, with the aim of obtaining a rigorous (mathematical) understanding of the semi-classical limit of the gravitational partition function. The paper surveys recent progress in the area, together with a selection of new results and open problems.
Optimizes ad pruning in sponsored search systems using reinforcement learning.
ADS filters data points for efficient batch active learning.
Deep learning has shown outstanding performance in identifying intricate structures in complex high-dimensional data, especially in the domain of computer vision. The application of deep learning to early detection and automated classification of Alzheimer's disease (AD) has recently gained considerable attention, as r…
Recurrent Neural Networks (RNNS) are now widely used on sequence generation tasks due to their ability to learn long-range dependencies and to generate sequences of arbitrary length. However, their left-to-right generation procedure only allows a limited control from a potential user which makes them unsuitable for int…
Study examines APOE's impact on AD progression using a novel DEBM approach.
ML helps select variables for minimum-variance portfolios, reducing risk and improving performance.
CAD-DA controls anomaly detection under domain adaptation.
STAND-DA improves AD in DA target domains with limited data.
Study on sensor fusion algorithms under high dimensional noise.
Diffusion models can memorize training data, limiting their creativity and privacy.
As an emerging research direction, online streaming feature selection deals with sequentially added dimensions in a feature space while the number of data instances is fixed. Online streaming feature selection provides a new, complementary algorithmic methodology to enrich online feature selection, especially targets t…
Boost-and-Skip generates minority samples without guidance, faster and more effectively.
New method reduces memorization in diffusion models without sacrificing image quality.
The purpose of the paper is two-fold: to introduce a multivariable creative telescoping method, and to apply it in a problem of Quantum Topology: namely the computation of the non-commutative -polynomial of twist knots. Our multivariable creative telescoping method allows us to compute linear recursions for sums of …
Invention involves combination, or more precisely, ratios of composition. According to Thomas Edison, "Genius is one percent inspiration and 99 percent perspiration" is an example. In many situations, researchers and inventors already have a variety of data and manage to create something new by using it, but the key pr…
Dropout improves GAN outputs by preserving input constraints.
Designing a logo for a new brand is a lengthy and tedious back-and-forth process between a designer and a client. In this paper we explore to what extent machine learning can solve the creative task of the designer. For this, we build a dataset -- LLD -- of 600k+ logos crawled from the world wide web. Training Generati…