arXiv research

Neural network detects sex trafficking ads from escort websites.

Deep RL team defends payloads from obstacles.

A family of replicator-like dynamics, called the escort replicator equation, is constructed using information-geometric concepts and generalized information entropies and diverenges from statistical thermodynamics. Lyapunov functions and escort generalizations of basic concepts and constructions in evolutionary game th…

This paper studies geometrical structure of the manifold of escort probability distributions and shows its new applicability to information science. In order to realize escort probabilities we use a conformal transformation that flattens so-called alpha-geometry of the space of discrete probability distributions, which…

Researchers explore gauge freedom in entropies of $q$-Gaussian measures.

Study of generalized Csiszár divergences and their application to Cramér-Rao bounds.

The paper generalizes Bayesian Cramér-Rao inequality using information geometry of relative α-entropy.

FEAT estimates free energy using adaptive transports.

New Stein identity for q-Gaussians reduces gradient variance in machine learning.

AIS algorithm improves heavy-tailed distribution estimation.

Perceptual ad-blocking is a novel approach that detects online advertisements based on their visual content. Compared to traditional filter lists, the use of perceptual signals is believed to be less prone to an arms race with web publishers and ad networks. We demonstrate that this may not be the case. We describe att…

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…

Study proposes an ad creative selection algorithm considering user fatigue.

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…

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…

Online audio advertising is a particular form of advertising used abundantly in online music streaming services. In these platforms, which tend to host tens of thousands of unique audio advertisements (ads), providing high quality ads ensures a better user experience and results in longer user engagement. Therefore, th…

E-commerce sponsored search contributes an important part of revenue for the e-commerce company. In consideration of effectiveness and efficiency, a large-scale sponsored search system commonly adopts a multi-stage architecture. We name these stages as ad retrieval, ad pre-ranking and ad ranking. Ad retrieval and ad pr…

Improves CTR prediction by considering spatial and temporal auxiliary ads.

Sharp Minkowski inequality found for AdS-Melvin spacetime surfaces.

A framework combines unsupervised and semi-supervised AD using synthetic anomalies.

Enhanced ad event prediction boosts performance.

The spacetime $AdS_2 \times S^2$ is well known to arise as the 'near horizon' geometry of the extremal Reissner-Nordstrom solution, and for that reason it has been studied in connection with the AdS/CFT correspondence. Here we consider asymptotically $AdS_2 \times S^2$ spacetimes that obey the null energy condition (or…

Landmark AD improves AD's efficiency without sacrificing performance.

New examples of Lie algebras with ad-invariant metrics found.

This study proves energy bounds in specific AdS spacetimes.

In this paper we present Percival, a browser-embedded, lightweight, deep learning-powered ad blocker. Percival embeds itself within the browser's image rendering pipeline, which makes it possible to intercept every image obtained during page execution and to perform blocking based on applying machine learning for image…

We formulate the variational problem for AdS gravity with Dirichlet boundary conditions and demonstrate that the covariant counterterms are necessary to make the variational problem well-posed. The holographic charges associated with asymptotic symmetries are then rederived via Noether's theorem and `covariant phase sp…

Study on uniqueness of ad-invariant metrics in Lie algebras.

Study identifies five AD subtypes using graph diffusion and similarity learning.

We study hyperideal polyhedra in the 3-dimensional anti-de Sitter space $AdS^3$, which are defined as the intersection of the projective model of $AdS^3$ with a convex polyhedron in $RP^3$ whose vertices are all outside of $AdS^3$ and whose edges all meet $AdS^3$. We show that hyperideal polyhedra in $AdS^3$ are unique…

AdS uniqueness and black hole energy bounds proven.

Optimizes bidding strategies for LinkedIn ads across multiple platforms.

Little is known about how different types of advertising affect brand attitudes. We investigate the relationships between three brand attitude variables (perceived quality, perceived value and recent satisfaction) and three types of advertising (national traditional, local traditional and digital). The data represent t…

Geometries and dual field theories linked by AdS/CFT.

Paper proposes bypassing implicit assumption in GM-based AD methods.

Crooked planes are piecewise linear surfaces that were introduced by Drumm in the early 1990s to construct fundamental domains for properly discontinuous actions of free groups on Minkowski 3-space. In a previous paper, we introduced analogues of these surfaces, called AdS crooked planes, in the 3-dimensional anti-de S…

The study constructs AdS manifolds from Gromov-Thurston manifolds.

The stability of physical systems depends on the existence of a state of least energy. In gravity, this is guaranteed by the positive energy theorem. For topological reasons this fails for nonsupersymmetric Kaluza-Klein compactifications, which can decay to arbitrarily negative energy. For related reasons, this also fa…

Alzheimer's disease (AD) is the most common neurodegenerative disease in older people. Despite considerable efforts to find a cure for AD, there is a 99.6% failure rate of clinical trials for AD drugs, likely because AD patients cannot easily be identified at early stages. This project investigated machine learning app…

Proposes a statistical test for VAE-based anomaly detection reliability.

Zero-shot anomaly detection method using batch normalization.

We study the causality relation in the 3-dimensional anti-de Sitter space AdS and its conformal boundary Ein. To any closed achronal subset $Λ$ in ${Ein}\_2$ we associate the invisible domain $E(Λ)$ from $Λ$ in AdS. We show that if $Γ$ is a torsion-free discrete group of isometries of AdS preserving $Λ$ and is non-elem…

The diagnosis of Alzheimer's disease (AD) in routine clinical practice is most commonly based on subjective clinical interpretations. Quantitative electroencephalography (QEEG) measures have been shown to reflect neurodegenerative processes in AD and might qualify as affordable and thereby widely available markers to f…

Study on numerical reliability of AD for MaxPool in neural nets.

New AD methods improve likelihood estimation for partially observed systems.

AD-HOC simplifies high-order derivative calculations in C++.

Deep AD on images outperforms traditional methods.

Click-through rate (CTR) prediction has been one of the most central problems in computational advertising. Lately, embedding techniques that produce low-dimensional representations of ad IDs drastically improve CTR prediction accuracies. However, such learning techniques are data demanding and work poorly on new ads w…