Grasping Student: semi-supervised learning for robotic manipulation

Gathering real-world data from the robot quickly becomes a bottleneck when constructing a robot learning system for grasping.

Polite Teacher: Semi-Supervised Instance Segmentation with Mutual Learning and Pseudo-Label Thresholding

We present Polite Teacher, a simple yet effective method for the task of semi-supervised instance segmentation.

On All-Action Policy Gradients

1 code implementation24 Oct 2022,

We decompose the variance of SPG and derive an optimality condition for all-action SPG.

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One Simple Trick to Fix Your Bayesian Neural Network

One of the most popular estimation methods in Bayesian neural networks (BNN) is mean-field variational inference (MFVI).

n-CPS: Generalising Cross Pseudo Supervision to n Networks for Semi-Supervised Semantic Segmentation

We present n-CPS - a generalisation of the recent state-of-the-art cross pseudo supervision (CPS) approach for the task of semi-supervised semantic segmentation.

Improved GQ-CNN: Deep Learning Model for Planning Robust Grasps

In this work we improve on one of the most promising approaches, the Grasp Quality Convolutional Neural Network (GQ-CNN) trained on the DexNet 2. 0 dataset.

Approximation and Parameterized Complexity of Minimax Approval Voting

Motivated by this, we then show a parameterized approximation scheme, running in time $\mathcal{O}^\star(\left({3}/{\epsilon}\right)^{2d})$, which is essentially tight assuming ETH.

Solving weighted and counting variants of connectivity problems parameterized by treewidth deterministically in single exponential time

It is well known that many local graph problems, like Vertex Cover and Dominating Set, can be solved in 2^{O(tw)}|V|^{O(1)} time for graphs G=(V, E) with a given tree decomposition of width tw.

Data Structures and Algorithms Computational Complexity Discrete Mathematics F.2.2; G.2.8

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