117 citations · 222 across the 24 of their papers we have counts for
24 papers
Gradient Descent Converges Linearly for Logistic Regression on Separable Data
Kyriakos Axiotis, Maxim Sviridenko
We show that running gradient descent with variable learning rate guarantees loss for the logistic regression objective, where the error decays…
Iterative Hard Thresholding with Adaptive Regularization: Sparser Solutions Without Sacrificing Runtime
Kyriakos Axiotis, Maxim Sviridenko
We propose a simple modification to the iterative hard thresholding (IHT) algorithm, which recovers asymptotically sparser solutions as a function of the condition number. When aim…
TSI: an Ad Text Strength Indicator using Text-to-CTR and Semantic-Ad-Similarity
Shaunak Mishra, Changwei Hu, Manisha Verma +3
Coming up with effective ad text is a time consuming process, and particularly challenging for small businesses with limited advertising experience. When an inexperienced advertise…
Local Search Algorithms for Rank-Constrained Convex Optimization
Kyriakos Axiotis, Maxim Sviridenko
We propose greedy and local search algorithms for rank-constrained convex optimization, namely solving given a convex function $R…
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding
Kyriakos Axiotis, Maxim Sviridenko
The goal of Sparse Convex Optimization is to optimize a convex function under a sparsity constraint , where is the target number of non-zero entries in a feas…
On the computational complexity of the probabilistic label tree algorithms
Robert Busa-Fekete, Krzysztof Dembczynski, Alexander Golovnev +4
Label tree-based algorithms are widely used to tackle multi-class and multi-label problems with a large number of labels. We focus on a particular subclass of these algorithms that…