49 citations · 131 across the 37 of their papers we have counts for
7 papers · 1 filter
Universal Spike Classifier
Muhammad Saif-ur-Rehman, Robin Lienkämper, Yaroslav Parpaley +8
In electrophysiology, microelectrodes are the primary source for recording neural data of single neurons (single unit activity). These microelectrodes can be implanted individually…
Challenges of Convex Quadratic Bi-objective Benchmark Problems
Tobias Glasmachers
Convex quadratic objective functions are an important base case in state-of-the-art benchmark collections for single-objective optimization on continuous domains. Although often co…
Challenges in High-dimensional Reinforcement Learning with Evolution Strategies
Nils Müller, Tobias Glasmachers
Evolution Strategies (ESs) have recently become popular for training deep neural networks, in particular on reinforcement learning tasks, a special form of controller design. Compa…
Dual SVM Training on a Budget
Sahar Qaadan, Merlin Schüler, Tobias Glasmachers
We present a dual subspace ascent algorithm for support vector machine training that respects a budget constraint limiting the number of support vectors. Budget methods are effecti…
Speeding Up Budgeted Stochastic Gradient Descent SVM Training with Precomputed Golden Section Search
Tobias Glasmachers, Sahar Qaadan
Limiting the model size of a kernel support vector machine to a pre-defined budget is a well-established technique that allows to scale SVM learning and prediction to large-scale d…
Multi-Merge Budget Maintenance for Stochastic Gradient Descent SVM Training
Sahar Qaadan, Tobias Glasmachers
Budgeted Stochastic Gradient Descent (BSGD) is a state-of-the-art technique for training large-scale kernelized support vector machines. The budget constraint is maintained increme…