Statistical Learning
Clustering for Continuous Event-based Eye Tracking Supplemental
Typically, human gaze movements are influenced by the effect of head movements i.e., the relationship
EyeGraph: Modularity-aware Spatio Temporal Graph Clustering for Continuous Event-based Eye Tracking
Our core idea is depicted in Figure 1.
On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks
Node individualization schemes, which assign unique identifiers to nodes (e.g., by adding random noise to features), are a common approach
NoiseGPT: Label Noise Detection and Rectification through Probability Curvature
Machine learning craves high-quality data which is a major bottleneck during realistic deployment, as it takes abundant resources and massive human labor to collect and label data. Unfortunately, label noise where image data mismatches with incorrect label exists ubiquitously in all kinds of datasets, significantly degrading the learning performance of deep networks. Learning with Label Noise (LNL) has been a common strategy for mitigating the influence of noisy labels.
Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems Kurt Butler
The TSCI approach is model-agnostic and can be used as a drop-in replacement for CCM and its generalizations.
Most Influential Subset Selection: Challenges, Promises, and Beyond Y uzheng Hu
Subset Selection (MISS) problem, which aims to identify a subset of training samples with the greatest collective influence.
], and simulating complex circuits
In particular, we consider the sparse linear regression task, i.e., the data is generated from a
Unlocking the Potential of Global Human Expertise
For example, in the Pandemic Response Challenge experiment, the context consisted of data about the geographic region for which the predictions were made, e.g., historical data of COVID-19 cases and intervention policies; actions were future schedules of intervention policies for the region; and outcomes were predicted future cases of COVID-19 along with the stringency