Prof. Rasmus Kyng — Research Profile
ETH Zurich · Department of Computer Science
About
Prof. Rasmus Kyng at ETH Zurich Department of Computer Science lists algorithms, convex optimization, graph algorithms, numerical linear algebra, fine-grained complexity theory, random matrix theory as their registered research area.
Research keywords
Recent papers
- A Practical Combinatorial Interior Point Method for Minimum-Cost FlowNewPreprintarXiv (Cornell University) · Oct 13
- A Simpler and Faster Min-Cost Flow Solver via Min-Ratio Cycles from Distance OraclesPreprintarXiv (Cornell University) · Sep 20
- Partially-Dynamic All-Pairs Maxflow and Effective Resistance via Stable SparsifiersPreprintarXiv (Cornell University) · Aug 26
From OpenAlex · papers whose author affiliation matches this university
Labs doing related research
Labs that recently published on topics this lab's recent papers share
Shared topic: Complexity and Algorithms in Graphs
Michael Kapralov 교수 연구실
EPFL · School of Computer and Communication Sciences
Constant-Factor Local Approximation for Bipartite Densest SubgraphNewPreprintarXiv (Cornell University) · Oct 16Alessandro Chiesa 교수 연구실
EPFL · School of Computer and Communication Sciences
Can AI Oversight Be Zero Knowledge?PreprintarXiv (Cornell University) · Oct 1Vera Traub 교수 연구실
ETH Zurich · Department of Computer Science
On the Bidirected Cut Relaxation for Steiner ForestMathematical Programming · Aug 12
Other labs in this department
- Adrian Perrig 교수 연구실
system and network security, networks, internet architecture
- Ana Klimovic 교수 연구실
cloud computing, operating systems, distributed systems, storage systems, computer architecture
- Andreas Krause 교수 연구실
machine learning, artificial intelligence, reinforcement learning, probabilistic inference
- Angelika Steger 교수 연구실
algorithms, combinatorics, randomization and probabilistic methods, combinatorial models for optimization
- April Yi Wang 교수 연구실
educational technology, human-computer interaction, artificial intelligence in education, collective intelligence and organizational technology, end-user programming, user interface for programming
- Bernhard Schölkopf 교수 연구실
machine learning, causal inference, applications in the sciences