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Found 8 papers, 2 papers with code
Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input
In this study, we document the performance of a set of advanced ML models in forecasting ED occupancy 24 hours ahead.
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction
Nonlinear dimensionality reduction of high-dimensional data is challenging as the low-dimensional embedding will necessarily contain distortions, and it can be hard to determine which distortions are the most important to avoid.
Scalable Probabilistic Matrix Factorization with Graph-Based Priors
The identification and removal of contested edges adds no computational complexity to state-of-the-art graph-regularized matrix factorization, remaining linear with respect to the number of non-zeros.
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(using extra training data)
Computing Stable Demers Cartograms
We enforce orthogonal separation constraints with linear programming, and measure quality in terms of keeping adjacent regions close (cartogram quality) and using similar positions for a region between the different data values (stability).
Computational Geometry Data Structures and Algorithms
Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off
In large graphs the necessary compromise is whether to differentiate colors sharply between locally occurring strongly bundled edges ("local bundles"), or also between the weakly bundled edges occurring globally over the graph ("global bundles"); we allow a user-set global-local tradeoff.
An Information Retrieval Approach to Finding Dependent Subspaces of Multiple Views
The basic CCA is restricted to maximizing a simple dependency criterion, correlation, measured directly between data coordinates.
Toward computational cumulative biology by combining models of biological datasets
A main challenge of data-driven sciences is how to make maximal use of the progressively expanding databases of experimental datasets in order to keep research cumulative.
Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning
Applications such as robot control and wireless communication require planning under uncertainty.
