345 papers with code • 0 benchmarks • 11 datasets
This new formulation leads to an algorithm that produces a stochastic classifier by playing a two-player non-zero-sum game solving for what we call a semi-coarse correlated equilibrium, which in turn corresponds to an approximately optimal and feasible solution to the constrained optimization problem.
Submodular maximization has become established as the method of choice for the task of selecting representative and diverse summaries of data.
We present a general framework for solving a large class of learning problems with non-linear functions of classification rates.
There has been remarkable progress on object detection and re-identification (re-ID) in recent years which are the key components of multi-object tracking.
Ranked #1 on Multi-Object Tracking on 2DMOT15 (using extra training data)