Demo Data from EDBT 2026 / reviewers in the wild / expert
Chris Rohlfs
dblp:202/6663 · also Christopher Rohlfs
· DBLP profile ↗
4ranked-venue papers
4as first author
3since 2021 · last 2025
0000-0001-7714-9231ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 4 first-author · 3 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational finance and economics · 100% | |
| Artificial intelligence
1 paper |
Information extraction and text analysis · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational finance and economics
financial forecasting |
0.2 | 1 | 2016 | The Effects of the Content of FOMC Communications on US Treasury Rates · EMNLP 2016 |
Computational finance and economics › financial data analysis
financial text analysis |
0.2 | 1 | 2016 | The Effects of the Content of FOMC Communications on US Treasury Rates · EMNLP 2016 |
Natural language and speech › Information extraction and text analysis › topic model
supervised topic model |
0.1 | 1 | 2016 | The Effects of the Content of FOMC Communications on US Treasury Rates · EMNLP 2016 |
Natural language and speech › Information extraction and text analysis
topic model |
0.1 | 1 | 2016 | The Effects of the Content of FOMC Communications on US Treasury Rates · EMNLP 2016 |
Methods — techniques the papers use, named apart from their topics
text classification · 0.5supervised topic modeling · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Generalization in neural networks: A broad survey
Chris Rohlfs |
Neurocomputing | 1 |
| 2023 | A descriptive analysis of olfactory sensation and memory in Drosophila and its relation to artificial neural networks
Chris Rohlfs |
Neurocomputing | 1 |
| 2023 | Problem-dependent attention and effort in neural networks with applications to image resolution and model selection
Chris Rohlfs |
Image Vis. Comput. | 1 |
| 2016 | The Effects of the Content of FOMC Communications on US Treasury RatesabstractThis study measures the effects of Federal Open Market Committee text content on the direction of short-and medium-term interest rate movements.Because the words relevant to short-and medium-term interest rates differ, we apply a supervised approach to learn distinct sets of topics for each dependent variable being examined.We generate predictions with and without controlling for factors relevant to interest rate movements, and our prediction results average across multiple training-test splits.Using data from 1999-2016, we achieve 93% and 64% accuracy in predicting Target and Effective Federal Funds Rate movements and 38%-40% accuracy in predicting longer term Treasury Rate movements.We obtain lower but comparable accuracies after controlling for other macroeconomic and market factors. Chris Rohlfs, Sunandan Chakraborty, Lakshminarayanan Subramanian |
EMNLP | 1 |