Bartering Books to Beers: a Recommender System for Exchange Platforms

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Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

In the chapter ``When to Introduce Electronic Trading Platforms in Over-the-Counter Markets?'' An equilibrium in a market is determined in which traders have the choice between using an electronic platform with a request-for-quote protocol or calling a dea ...

We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its mutual information when the tensor is of even order. The proof uses the adaptive interpolation method, for which rank-on ...

In this work, we propose a new, fast and scalable method for anomaly detection in large time-evolving graphs. It may be a static graph with dynamic node attributes (e.g. time-series), or a graph evolving in time, such as a temporal network. We define an an ...

The computation and modeling of extents has been proposed to handle the complexity of large-scale model identification tasks. Unfortunately, the existing extent-based framework only applies when certain conditions apply. Most typically, it is required that ...

Many data-intensive applications require real-time analytics over streaming data. In a growing number of domains -- sensor network monitoring, social web applications, clickstream analysis, high-frequency algorithmic trading, and fraud detections to name a ...

In many graph–mining problems, two networks from different domains have to be matched. In the absence of reliable node attributes, graph matching has to rely on only the link structures of the two networks, which amounts to a generalization of the classic ...

In our daily lives, our mobile phones sense our movements and interactions via a rich set of embedded sensors such as a GPS, Bluetooth, accelerometers, and microphones. This enables us to use mobile phones as agents for collecting spatio-temporal data. The ...

We propose a vector space approach for inverse rendering of a Lambertian convex object with distant light sources. In this problem, the texture of the object and arbitrary lightings are both to be recovered from multiple images of the object and its 3D mod ...

The generation of synthetic populations through simulation methods is an important research topic and has a key application in agent-based modeling of transport and land use. The next step in this research area is the generation of complete synthetic house ...

Many analytics tasks and machine learning problems can be naturally expressed by iterative linear algebra programs. In this paper, we study the incremental view maintenance problem for such complex analytical queries. We develop a framework, called LINVIEW ...

Bilinear models of count data with Poisson distribution are popular in applications such as matrix factorization for recommendation systems, modeling of receptive fields of sensory neurons, and modeling of neural-spike trains. Bayesian inference in such mo ...

The advent of online social networks created new prediction opportunities for recommender systems: instead of relying on past rating history through the use of collaborative filtering (CF), they can leverage the social relations among users as a predictor ...

Graph matching is a generalization of the classic graph isomorphism problem. By using only their structures a graph-matching algorithm finds a map between the vertex sets of two similar graphs. This has applications in the de-anonymization of social and in ...

Bartering Books to Beers: a Recommender System for Exchange Platforms

Chat with Graph Search

Dynamic Personalized Ranking

Discrete-Choice Mining of Social Processes

Trading mechanisms in over-the-counter markets

Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization

Anomaly detection in the dynamics of web and social networks

Incremental Parameter Estimation under Rank-Deficient Measurement Conditions

Efficient Incremental Data Analysis

Growing a Graph Matching from a Handful of Seeds

Population Sensing Using Mobile Devices : a Statistical Opportunity or a Privacy Nightmare?

Inverse Rendering of Lambertian Surfaces Using Subspace Methods

Association Generation in Synthetic Population for Transportation Applications: Graph-Theoretic Solution

LINVIEW: Incremental View Maintenance for Complex Analytical Queries

Variational Gaussian Inference for Bilinear Models of Count Data

Comparing the Predictive Capability of Social and Interest Affinity for Recommendations

On the Performance of Percolation Graph Matching