Hand-picked collection of articles, papers, books, journals, and guides from major sources, publishers, and institutions worth your time.
Ron Yurko, director of the Carnegie Mellon Sports Analytics Center, explains how data is reshaping the Heisman race, college football forecasting, and sports betting.…Read More
Autonomous driving is a cornerstone technology for the future of intelligent transportation, where end-to-end learning has emerged as a transformative paradigm that directly maps multimodal sensory inputs to driving actions through unified differentiable models. While offering…
We apply recurrent neural networks (RNN) on a new domain, namely recommender systems. Real-life recommender systems often face the problem of having to base recommendations only on short session-based data (e.g. a small sportsware website) instead of long user histories (as in…
Most real-world datasets are inherently heterogeneous graphs, which involve a diversity of node and relation types. Heterogeneous graph embedding is to learn the structure and semantic information from the graph, and then embed it into the low-dimensional node representation…
Click-through rate (CTR) prediction is a critical task in online advertising systems. Existing works mainly address the single-domain CTR prediction problem and model aspects such as feature interaction, user behavior history and contextual information. Nevertheless, ads are…
This paper proposes a framework for modeling probability of default via functional data analysis. By representing a series of credit variables as functions, we investigate whether intra-monthly information improves default predictability in linear models. We further show how a…
Many search systems work with large amounts of natural language data, e.g., search queries, user profiles and documents, where deep learning based natural language processing techniques (deep NLP) can be of great help. In this paper, we introduce a comprehensive study of…
Speech At the Istanbul Economic Forum, Central Bank of the Republic of Türkiye, Istanbul, Türkiye
Roy Fielding (the inventor of REST)
Professor R. Jisung Park discusses climate change and the impact of extreme heat on academic success and worker productivity.…Read More
PPaint/Ikon Images Dry rot. A Potemkin village. The Wizard of Oz. What do those things have in common? In each case, they may look good on the surface, but it’s only an illusion. Wood afflicted with dry rot looks just fine until the tree it’s in topples down. Grigory Potemkin…
ISC Stormcast For Monday, October 5th, 2026 https://isc.sans.edu/podcastdetail/10122, Author: Johannes Ullrich
ISC Stormcast For Wednesday, September 30th, 2026 https://isc.sans.edu/podcastdetail/10116, Author: Johannes Ullrich
Learning effective feature crosses is the key behind building recommender systems. However, the sparse and large feature space requires exhaustive search to identify effective crosses. Deep & Cross Network (DCN) was proposed to automatically and efficiently learn bounded-degree…
In this work, we present the findings of an online study, where we explore the impact of utilizing embeddings to recommend job postings under real-time constraints. On the Austrian job platform Studo Jobs, we evaluate two popular recommendation scenarios: (i) providing similar…
We're looking to hear from people involved in evaluating, selecting or adopting EASM.
Danae Diaz/Ikon Images It’s a familiar scenario: An organization implements digital tools intended to improve a particular process but fails to obtain the desired result. Employees who are meant to use them complain that the tools don’t solve the problem or that they add…
We study libraries of cross-sectional signals: at each date, a forecast vector over $d$ assets intended to predict the next period's cross-sectional return. Demeaned and unit-normalized, a signal is a point on a sphere and its $T$-date history a point on a product of $T$…
Bank treasury portfolios must balance yield, liquidity, and interest-rate risk across bonds of different maturities. Static allocation rules are ill-suited to this task: portfolios concentrated in long-duration securities with no dynamic adjust- ment mechanism can accumulate…
We develop a diffusion-model framework for dynamic implied-volatility surface generation and evaluate its economic usefulness through data-driven hedging. The framework consists of two models. AD-Seq-Vol jointly learns the conditional evolution of the underlying asset return…