arXiv research

Study analyzes factors influencing healthcare providers' engagement with SMS campaigns.

Proposes a greedy algorithm for telecom offers to retain subscribers.

In this paper, a novel architecture of Recurrent Neural Network (RNN) is designed and experimented. The proposed RNN adopts a computational memory based on the concept of stigmergy. The basic principle of a Stigmergic Memory (SM) is that the activity of deposit/removal of a quantity in the SM stimulates the next activi…

Spectral mixture (SM) kernels comprise a powerful class of generalized kernels for Gaussian processes (GPs) to describe complex patterns. This paper introduces model compression and time- and phase (TP) modulated dependency structures to the original (SM) kernel for improved generalization of GPs. Specifically, by adop…

Study geodesic flows, billiards, and metrics on manifolds.

For a given smooth compact manifold $M$, we introduce an open class $\mathcal G(M)$ of Riemannian metrics, which we call \emph{metrics of the gradient type}. For such metrics $g$, the geodesic flow $v^g$ on the spherical tangent bundle $SM \to M$ admits a Lyapunov function (so the $v^g$-flow is traversing). It turns ou…

HapNet predicts marketing campaign effects using a hierarchical structure.

New taxonomy for structured missingness in large-scale databases.

With the success of modern machine learning, it is becoming increasingly important to understand and control how learning algorithms interact. Unfortunately, negative results from game theory show there is little hope of understanding or controlling general n-player games. We therefore introduce smooth markets (SM-game…

Improves learning of spectral mixture kernels with approximate Bayesian inference.

We establish, via geometric quantization of the supercotangent bundle sM of (M,g), a correspondence between its conformal geometry and those of the spinor bundle. In particular, the Kosmann Lie derivative of spinors is obtained by quantization of the comoment map, associated to the new Hamiltonian action of conf(M,g) o…

Adaptive filters are applied in several electronic and communication devices like smartphones, advanced headphones, DSP chips, smart antenna, and teleconference systems. Also, they have application in many areas such as system identification, channel equalization, noise reduction, echo cancellation, interference cancel…

Score matching fails to train VAEs robustly, revealing autoencoding loss insights.

Paper introduces a new distributional successor measure for reinforcement learning.

Let $M$ be a compact smooth Riemannian $n$-manifold with boundary. We combine Gromov's amenable localization technique with the Poincaré duality to study the {\sf traversally generic} geodesic flows on $SM$, the space of the spherical tangent bundle. Such flows generate stratifications of $SM$, governed by rich univers…

Real-Time Bidding is nowadays one of the most promising systems in the online advertising ecosystem. In the presented study, the performance of RTB campaigns is improved by optimising the parameters of the users' profiles and the publishers' websites. Most studies about optimising RTB campaigns are focused on the biddi…

This paper enhances uplift modeling for multi-treatment marketing campaigns.

This study shows neural nets can approximate Turing machines with meaningful statistical properties.

Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control systems and machinery, these adversarial errors could grow to be a serious problem. Despite numerous studies over the past few years, the field of…

Real time bidding (RTB) enables demand side platforms (bidders) to scale ad campaigns across multiple publishers affiliated to an RTB ad exchange. While driving multiple campaigns for mobile app install ads via RTB, the bidder typically has to: (i) maintain each campaign's efficiency (i.e., meet advertiser's target cos…

An average adult is exposed to hundreds of digital advertisements daily (https://www.mediadynamicsinc.com/uploads/files/PR092214-Note-only-150-Ads-2mk.pdf), making the digital advertisement industry a classic example of a big-data-driven platform. As such, the ad-tech industry relies on historical engagement logs (clic…

Semi-Implicit Variational Inference (SIVI) is improved with SIVI-SM using score matching.

Study uses causal machine learning to assess coupon campaign impact on retailer sales.

Study optimizes classifiers for credit card mail campaigns and default prediction.

Efficiently approximates higher-order derivatives for generative models.

This paper optimizes ad bids and daily budgets for multiple campaigns in pay-per-click advertising.

The study shows conditions for thermostats to have no conjugate points.

Truncated densities are probability density functions defined on truncated domains. They share the same parametric form with their non-truncated counterparts up to a normalizing constant. Since the computation of their normalizing constants is usually infeasible, Maximum Likelihood Estimation cannot be easily applied t…

The paper tackles budget allocation for multiple campaigns using a novel combinatorial bandit approach.

Hidden Markov Model (HMM) combined with Gaussian Process (GP) emission can be effectively used to estimate the hidden state with a sequence of complex input-output relational observations. Especially when the spectral mixture (SM) kernel is used for GP emission, we call this model as a hybrid HMM-GPSM. This model can e…

SM-netFusion estimates brain network atlas by considering multiple topological measures.

Smart Meters (SMs) are able to share the power consumption of users with utility providers almost in real-time. These fine-grained signals carry sensitive information about users, which has raised serious concerns from the privacy viewpoint. In this paper, we focus on real-time privacy threats, i.e., potential attacker…

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…

New methods help calibrate complex ABMs more efficiently.

We propose an computational framework for real-time risk assessment and prioritizing for random outcomes without prior information on probability distributions. The basic model is built based on satisficing measure (SM) which yields a single index for risk comparison. Since SM is a dual representation for a family of r…

PolicySynth improves synthetic data alignment with real data for better campaign decisions.

Extending braid group representations to singular braid monoids and groups.

New method uses SURE to denoise signals, outperforming NPMLE.

Activists align with large fund preferences for success.

Paper addresses CPA line forecasting in online advertising mid-flight.

Optimizes user marketing campaigns to balance cost and effectiveness.

Proves lower bounds on Hausdorff dimension of projections of invariant sets.

The paper tackles decision making problems with funnel structure in email marketing campaigns.

This paper addresses the problem of inferring a regular expression from a given set of strings that resembles, as closely as possible, the regular expression that a human expert would have written to identify the language. This is motivated by our goal of automating the task of postmasters of an email service who use r…

Framework detects influential actors in disinformation networks.

Enhances GPLVM for multi-view data with scalable latent representation learning.

Mobile payment incentives optimized using merchant transaction networks.

Chagas disease is a neglected disease, and information about its geographical spread is very scarse. We analyze here mobility and calling patterns in order to identify potential risk zones for the disease, by using public health information and mobile phone records. Geolocalized call records are rich in social and mobi…