arXiv research

The paper proposes a method to test properties of the optimal assortment in multinomial logit models.

Triangle fees adjust fees based on trade size and price movement, improving price accuracy and revenue.

Study optimal auction formats for maximizing MEV on Ethereum.

Proposes a revenue function to evaluate dendrograms from comparisons.

Paper shows re-solving heuristics have constant regret for price-based revenue management.

Tax evasion is the illegal evasion of taxes by individuals, corporations, and trusts. The revenue loss from tax avoidance can undermine the effectiveness and equity of the government policies. A standard measure of tax evasion is the tax gap, that can be estimated as the difference between the total amounts of tax theo…

This paper examines and proposes several attribution modeling methods that quantify how revenue should be attributed to online advertising inputs. We adopt and further develop relative importance method, which is based on regression models that have been extensively studied and utilized to investigate the relationship …

Paper optimizes liquidity provision in decentralized finance markets.

A new algorithm COVA-FC improves subgroup-fair clustering efficiency.

As shown in recent research, deep neural networks can perfectly fit randomly labeled data, but with very poor accuracy on held out data. This phenomenon indicates that loss functions such as cross-entropy are not a reliable indicator of generalization. This leads to the crucial question of how generalization gap should…

Develops a method to optimize tax codes with practical constraints.

The paper proposes a machine learning technique to optimize prices in fashion e-commerce.

The study analyzes how cross-chain interoperability affects decentralized lending protocols' performance.

We analyze annual revenues and earnings data for the 500 largest-revenue U.S. companies during the period 1954-2007. We find that mean year profits are proportional to mean year revenues, exception made for few anomalous years, from which we postulate a linear relation between company expected mean profit and revenue. …

Out of the companies, Dolby is the company with the best overall financial and operation health. According to the table that accounted its financial statements for the past three years, Dolby has stable profit margins that generates a revenue in the billions, the only company in ten figures. Corporate competition to ga…

In the cost per click (CPC) pricing model, an advertiser pays an ad network only when a user clicks on an ad; in turn, the ad network gives a share of that revenue to the publisher where the ad was impressed. Still, advertisers may be unsatisfied with ad networks charging them for "valueless" clicks, or so-called accid…

We present novel understandings of the Gamma-Poisson (GaP) model, a probabilistic matrix factorization model for count data. We show that GaP can be rewritten free of the score/activation matrix. This gives us new insights about the estimation of the topic/dictionary matrix by maximum marginal likelihood estimation. In…

Study shows local governments smooth fiscal shocks from property tax revenues.

This paper optimizes revenue and resource balance in network revenue management.

Paper forecasts tax revenues in Bulgaria during pandemic.

Recent research has used margin theory to analyze the generalization performance for deep neural networks (DNNs). The existed results are almost based on the spectrally-normalized minimum margin. However, optimizing the minimum margin ignores a mass of information about the entire margin distribution, which is crucial …

Uplift models support decision-making in marketing campaign planning. Estimating the causal effect of a marketing treatment, an uplift model facilitates targeting communication to responsive customers and efficient allocation of marketing budgets. Research into uplift models focuses on conversion models to maximize inc…

A scalable model estimates revenue uncertainty for SMEs.

Proposes robust assortment optimization from observational data.

New offline RL method works with limited data and function approximators.

Germany's tax admin costs likely exceed 20% of total revenue, requiring system improvement.

Near-Exponential Convergence Rates for kNN Classification

Study finds tax avoidance and IT issues hinder revenue in Gombe state.

The paper proposes a new method for product recommendation that considers revenue contributions and user similarity.

Research analyzes Georgia's tax system and suggests improvements.

Model for dynamic pricing across multiple RE groups to maximize revenue.

'There is no terror in the bang, only is the anticipation of it' - Alfred Hitchcock. Yet there is everything in correctly anticipating the bang a movie would make in the box-office. Movies make a high profile, billion dollar industry and prediction of movie revenue can be very lucrative. Predicted revenues can be used …

The paradox of the energy transition is that the low marginal costs of new renewable energy sources (RES) drag electricity prices down and discourage investments in flexible productions that are needed to compensate for the lack of dispatchability of the new RES. The energy transition thus discourages the investments t…

Study on tax administration issues and their impact on Georgia's budget revenues.

This paper optimizes multi-channel sequential advertising to maximize cumulative revenue.

This paper addresses the problem of unsupervised domain adaption from theoretical and algorithmic perspectives. Existing domain adaptation theories naturally imply minimax optimization algorithms, which connect well with the domain adaptation methods based on adversarial learning. However, several disconnections still …

In this paper, we reformulate the forest representation learning approach as an additive model which boosts the augmented feature instead of the prediction. We substantially improve the upper bound of generalization gap from $\mathcal{O}(\sqrt\frac{\ln m}{m})$ to $\mathcal{O}(\frac{\ln m}{m})$, while $λ$ - the margin r…

This study improves valuation of post-revenue biopharmaceutical assets using Pfizer's data.

Proposes balancing revenue and environmental impact in assortment planning.

The study uses historical revenue data to forecast music catalog cashflows and multipliers.

Optimizes web publisher revenues from RTB auctions.

For any business, planning is a continuous process, and typically business-owners focus on making both long-term planning aligned with a particular strategy as well as short-term planning that accommodates the dynamic market situations. An ability to perform an accurate financial forecast is crucial for effective plann…

Study learns optimal auctions from corrupted or perturbed bidder valuation samples.

This paper improves bidding price prediction for ancillary services markets, boosting revenues.

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…

This work studies learning curves for revenue maximization algorithms.

Online advertisement is the main source of revenue for Internet business. Advertisers are typically ranked according to a score that takes into account their bids and potential click-through rates(eCTR). Generally, the likelihood that a user clicks on an ad is often modeled by optimizing for the click through rates rat…

Optimal design for multinomial logit models improves assortment selection efficiency.