Demo Data from EDBT 2026 / reviewers in the wild / expert
Nicholas Modly
dblp:41/10570
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1
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.
| Computer graphics and multimedia
1 paper |
Rendering · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Rendering › rendering optimization
shader optimization |
0.1 | 1 | 2011 | Genetic programming for shader simplification · ACM Trans. Graph. 2011 |
Methods — techniques the papers use, named apart from their topics
perceptual error metrics · 0.1genetic programming · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Genetic programming for shader simplificationabstractWe present a framework based on Genetic Programming (GP) for automatically simplifying procedural shaders. Our approach computes a series of increasingly simplified shaders that expose the inherent trade-off between speed and accuracy. Compared to existing automatic methods for pixel shader simplification [Olano et al. 2003; Pellacini 2005], our approach considers a wider space of code transformations and produces faster and more faithful results. We further demonstrate how our cost function can be rapidly evaluated using graphics hardware, which allows tens of thousands of shader variants to be considered during the optimization process. Our approach is also applicable to multi-pass shaders and perceptual-based error metrics. Pitchaya Sitthi-amorn, Nicholas Modly, Westley Weimer, Jason Lawrence |
ACM Trans. Graph. | 2 |