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Found 9 papers, 3 papers with code
Connectivity Oracles for Predictable Vertex Failures
It is already well understood: previous works [Duan--Pettie STOC'10; Long--Saranurak FOCS'22] achieve query time linear in the number of failed vertices, and it is conditionally optimal as long as we require preprocessing time polynomial in the size of the graph and update time polynomial in the number of failed vertices.
Mixing predictions for online metric algorithms
Since the performance of each predictor may vary over time, it is desirable to use not the single best predictor as a benchmark, but rather a dynamic combination which follows different predictors at different times.
Paging with Succinct Predictions
We consider two natural such setups: (i) discard predictions, in which the predicted bit denotes whether or not it is ``safe'' to evict this page, and (ii) phase predictions, where the bit denotes whether the current page will be requested in the next phase (for an appropriate partitioning of the input into phases).
Learning-Augmented Maximum Flow
We present an algorithm that, given an $m$-edge flow network and a predicted flow, computes a maximum flow in $O(m\eta)$ time, where $\eta$ is the $\ell_1$ error of the prediction, i. e., the sum over the edges of the absolute difference between the predicted and optimal flow values.
Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds
A key ingredient in our approach is a new algorithm for the online ski rental problem in the learning augmented setting with tight dependence on the prediction error.
Nearly-Tight and Oblivious Algorithms for Explainable Clustering
We give an algorithm that outputs an explainable clustering that loses at most a factor of $O(\log^2 k)$ compared to an optimal (not necessarily explainable) clustering for the $k$-medians objective, and a factor of $O(k \log^2 k)$ for the $k$-means objective.
Robust Learning-Augmented Caching: An Experimental Study
Effective caching is crucial for the performance of modern-day computing systems.
Online metric algorithms with untrusted predictions
Still, decision-making systems that are based on such predictors need not only to benefit from good predictions but also to achieve a decent performance when the predictions are inadequate.
Data Structures and Algorithms
Emotion Recognition Using Wearables: A Systematic Literature Review Work in progress
Wearables like smartwatches or wrist bands equipped with pervasive sensors enable us to monitor our physiological signals.
