Research
On-device research index

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.

168,982 papers · 148 categories

Trend · papers per month

25497498 · Jun 202019922001200920172026
48 results for food ingredient pairings

KitcheNette predicts and recommends food ingredient pairings.

problem Limited study of food ingredient pairings despite many existing pairings.
method Siamese neural networks trained on a dataset of 300K scores.
result KitcheNette outperforms other models and discovers novel pairings.

Deep learning system improves accuracy of food packaging date verification.

problem Improper labeling of food packaging poses health risks.
method Multi-source deep domain adaptation for domain-invariant representations and class boundary alignment.
result Significant improvement in classification accuracy of use-by date verification.

For the first time, we apply the wavelet coherence methodology on biofuels (ethanol and biodiesel) and a wide range of related commodities (gasoline, diesel, crude oil, corn, wheat, soybeans, sugarcane and rapeseed oil). This way, we are able to investigate dynamics of correlations in time and across scales (frequencie…

2012-09-05abs ↗pdf ↗

Over the past decade, the stellar growth of Indian economy has been challenged by persistently high levels of inflation, particularly in food prices. The primary reason behind this stubborn food inflation is mismatch in supply-demand, as domestic agricultural production has failed to keep up with rising demand owing to…

2017-01-30abs ↗pdf ↗

Recent droughts in the midwestern United States threaten to cause global catastrophe driven by a speculator amplified food price bubble. Here we show the effect of speculators on food prices using a validated quantitative model that accurately describes historical food prices. During the last six years, high and fluctu…

2012-09-27abs ↗pdf ↗

Paper compares machine learning models for food authenticity.

problem Determining correct food labelling from NIR spectroscopic data.
method Applied and compared various classification, dimension reduction, and variable selection approaches to NIR datasets of meat, olive oil, and honey samples.
result Partial least squares outperformed other approaches in classifying food authenticity.

Increases in global food prices have led to widespread hunger and social unrest---and an imperative to understand their causes. In a previous paper published in September 2011, we constructed for the first time a dynamic model that quantitatively agreed with food prices. Specifically, the model fit the FAO Food Price I…

2012-03-06abs ↗pdf ↗

Wavelet analysis reveals financialization effects on oil-food price correlation.

problem Investigating the correlation between oil and food prices and their determinants.
method Wavelet analysis and energy-based measures to differentiate high and low frequency movements.
result Significant local correlation between food and oil is due to financialization and emerging economies' demand.

Study reveals clusters of resilient and vulnerable Spanish agri-food firms post-Ukraine-Russia war.

problem Financial resilience of agri-food companies in Spain during the Ukraine-Russia conflict.
method Cluster analysis using centred log-ratios for compositional data of financial ratios.
result Increase in resilient firms by 2023, highlighting sectoral adaptation to economic challenges.

Machine learning models are vulnerable to adversarial examples. An adversary modifies the input data such that humans still assign the same label, however, machine learning models misclassify it. Previous approaches in the literature demonstrated that adversarial examples can even be generated for the remotely hosted m…

2018-05-03abs ↗pdf ↗

Algorithm improves resource allocation for food outreach to homeless.

problem Resource-constrained outreach for homeless individuals and food rescue.
method Thompson sampling with Markov chain recovery (via Stein variational gradient descent) for partially-observed episodic restless bandits.
result Significantly outperforms baselines in both organizations' problems.

Deep learning model reduces food waste by stabilizing online food delivery supply chains.

problem Wastage and bullwhip effect in online food delivery services.
method Two-phase LSTM network for demand forecasting, newsvendor model for inventory management.
result Significant reduction in bullwhip effect and food waste, improved forecasting accuracy.

Study predicts purchasing decisions of online food delivery customers.

problem Understanding and predicting consumer purchasing decisions in online food delivery.
method Used machine learning techniques including CART, C4.5, random forest, and rule-based classifiers to predict purchasing decisions.
result C4.5 decision tree model outperformed others with 91.67% accuracy.

Technical report predicts eating and food purchasing behaviors of free-living individuals.

problem Predicting eating and food purchasing behaviors of free-living individuals.
method Applied multiple machine learning algorithms (Logistic Regression, RBF-SVM, Random Forest, Gradient Boosting) to minute-level features from sensors and environmental context.
result Gradient Boosting model had the highest mean accuracy score (0.7289) for predicting eating events before 0 to 4 minutes.

Improved sales forecasting for new products using transfer learning.

problem Insufficient training data for new products leads to inaccurate sales forecasts.
method Network-based Transfer Learning approach for deep neural networks.
result Deep neural networks' prediction accuracy for food sales forecasting can be effectively increased.

Nemesyst optimizes deep learning for IoT food refrigeration systems.

problem Optimizing deep learning for large-scale IoT systems with dynamic data.
method Hybrid parallelism framework using databases and model sequentialisation.
result Demonstrated compelling performance of deep learning models in IoT food refrigeration.

Study finds WACC negatively impacts firm profitability in Bangladesh's food industry.

problem Determining the impact of Weighted Average Cost of Capital (WACC) on firm profitability.
method Fixed Effects Panel Regression Model using 12 food and allied industry companies from 2005-2019.
result WACC negatively correlates with firm profitability (ROA), significant relationship.

Conversion of corn to ethanol in the US since 2005 has been a major cause of global food price increases during that time and has been shown to be ineffective in achieving US energy independence and reducing environmental impact. We make three key statements to enhance understanding and communication about ethanol prod…

2012-10-22abs ↗pdf ↗

Researchers develop a machine learning model to improve smell perception for food quality monitoring.

problem Limited data in target domain makes it hard to accurately classify food quality.
method Weakly supervised domain adaptation framework using multiple models in supervised and unsupervised settings.
result The approach generalizes well from one domain to another, improving food quality classification.

The waggle dance that honeybees perform is an astonishing way of communicating the location of food source. After over 60 years of its discovery, researchers still use manual labeling by watching hours of dance videos to detect different transitions between dance components thus extracting information regarding the dis…

2017-05-20abs ↗pdf ↗

Paper calculates Torelli group's cohomology second group.

problem Calculating the second rational cohomology group of the Torelli group.
method Building on Hain's and Kupers-Randal-Williams's work, the paper provides an exposition of prerequisite material and the two key results.
result Calculation of the second rational cohomology group of the Torelli group.

Research shows franchised fast food companies' stock prices decline more during recessions.

problem Impact of recession on franchised fast food companies' stock prices.
method Analyzed stock price data with Weibull distribution.
result Recessions have a more severe impact on franchised fast food companies' stock prices.

We give a new proof of the theorem of Birman-Powell that the Torelli subgroup of the mapping class group of a closed orientable surface of genus at least 3 is generated by simple homeomorphisms known as bounding pair maps. The key ingredient is a proof that the subcomplex of the curve complex of the surface spanned by …

2011-10-05abs ↗pdf ↗

We study chirally cosmetic surgeries, that is, a pair of Dehn surgeries on a knot producing homeomorphic 3-manifolds with opposite orientations. Several constraints on knots and surgery slopes to admit such surgeries are given. Our main ingredients are the original and the SL(2,C)SL(2,\mathbb{C}) version of Casson invariant…

2017-07-01abs ↗pdf ↗

We propose a method to construct G_2-instantons over a compact twisted connected sum G_2-manifold, applying a gluing result of Sá Earp and Walpuski to instantons over a pair of 7-manifolds with a tubular end (see arXiv:1310.7933). In our example, the moduli spaces of the ingredient instantons are non-trivial, and their…

2015-10-13abs ↗pdf ↗