Graph Bisection Algorithm
An algorithm that partitions the vertices of a graph into two disjoint subsets while minimizing the number of edges between the subsets.
Tag: Technique
Reward Profiling
A method for selectively updating the policy based on high-confidence performance estimations to improve the stability and convergence of reinforcement learning algorithms.
Predictive Sensing Inference
Inference strategies tailored to improve model performance on specific benchmarks by predicting sensory information.
NoSense
A baseline model that discards temporal structure and utilizes a bag-of-words approach with SigLIP for video analysis.
SigLIP
A model that uses a bag-of-words approach for processing video data, focusing on significant visual features.
Policy Gradient
A class of algorithms in reinforcement learning that optimize the policy directly by adjusting the parameters in the direction of the gradient of expected reward.
Sparsity-Aware Retraining
A retraining process that takes into account the sparsity of the model, focusing on recovering performance without reactivating pruned connections.
One-Shot Pruning
A pruning strategy that eliminates weights in a single pass rather than through iterative cycles of training and pruning.
Unstructured Pruning
A method of reducing the size of neural networks by removing individual weights based on certain criteria, rather than entire neurons or layers.
Knowledge Distillation
A process where a smaller model is trained to replicate the behavior of a larger, pre-trained model, effectively transferring knowledge.