Structural bootstrapping—A novel, generative mechanism for faster and more efficient acquisition of action-knowledge F Wörgötter, C Geib, M Tamosiunaite, EE Aksoy, J Piater, H Xiong, A Ude, ... IEEE Transactions on Autonomous Mental Development 7 (2), 140-154, 2015 | 34 | 2015 |
Discriminative topic modeling with logistic LDA I Korshunova, H Xiong, M Fedoryszak, L Theis Advances in neural information processing systems 32, 2019 | 25 | 2019 |
Diversity priors for learning early visual features H Xiong, AJ Rodríguez-Sánchez, S Szedmak, J Piater Frontiers in computational neuroscience 9, 104, 2015 | 13 | 2015 |
A Study of Point Cloud Registration with Probability Product Kernel Functions H Xiong, S Szedmak, J Piater 2013 International Conference on 3D Vision, 207-214, 2013 | 11 | 2013 |
Scalable, accurate image annotation with joint SVMs and output kernels H Xiong, S Szedmak, J Piater Neurocomputing 169, 205-214, 2015 | 10 | 2015 |
Towards sparsity and selectivity: Bayesian learning of restricted Boltzmann machine for early visual features H Xiong, S Szedmak, A Rodríguez-Sánchez, J Piater Artificial Neural Networks and Machine Learning–ICANN 2014: 24th …, 2014 | 9 | 2014 |
Reducing redundancy and model decay with embeddings D Shiebler, L Belli, J Baxter, H Xiong, A Tayal US Patent App. 16/271,630, 2019 | 6 | 2019 |
Multi-label object categorization using histograms of global relations W Mustafa, H Xiong, D Kraft, S Szedmak, J Piater, N Krüger 2015 International Conference on 3D Vision, 309-317, 2015 | 6 | 2015 |
Homogeneity analysis for object-action relation reasoning in kitchen scenarios H Xiong, S Szedmak, J Piater 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap …, 2013 | 6 | 2013 |
Learning missing edges via kernels in partially-known graphs. S Krivic, S Szedmak, H Xiong, JH Piater ESANN, 2015 | 5 | 2015 |
Fighting redundancy and model decay with embeddings D Shiebler, L Belli, J Baxter, H Xiong, A Tayal arXiv preprint arXiv:1809.07703, 2018 | 4 | 2018 |
Learning V4 curvature cell populations from sparse endstopped cells A Rodríguez-Sánchez, S Oberleiter, H Xiong, J Piater Artificial Neural Networks and Machine Learning–ICANN 2016: 25th …, 2016 | 4 | 2016 |
Rotation Optimization on the Unit Quaternion Manifold and its Application for Robotic Grasping P Zech, H Xiong, J Piater IMA Conference on Mathematics of Robotics. IMA, 2015 | 3 | 2015 |
Implicit Learning of Simpler Output Kernels for Multi-Label Prediction H Xiong, S Szedmak, J Piater NIPS workshop on Representation and Learning for Complex Outputs 5, 2014 | 3 | 2014 |
Efficient, General Point Cloud Registration With Kernel Feature Maps H Xiong, S Szedmak, J Piater 2013 International Conference on Computer and Robot Vision (CRV), 83 - 90, 2013 | 3 | 2013 |
3D Object Class Geometry Modeling with Spatial Latent Dirichlet Markov Random Fields H Xiong, S Szedmak, J Piater 2013 German Conference on Pattern Recognition, 51-60, 2013 | 2 | 2013 |
Comparing Binary Hamiltonian Monte Carlo and Gibbs Sampling for Training Discrete MRFs with Stochastic Approximation H Xiong, S Szedmak, J Piater AISTATS, 2014 | 1 | 2014 |
Learning Interrelations via Incomplete Multi-valued Mappings Technical Report S Szedmak, H Xiong, S Krivic Training 1, y1, 2018 | | 2018 |
Active and Transfer Learning of Grasps by Kernel Adaptive MCMC P Zech, H Xiong, J Piater arXiv preprint arXiv:1611.06368, 2016 | | 2016 |
Learning undirected graphical models using persistent sequential Monte Carlo H Xiong, S Szedmak, J Piater Machine Learning 103, 239-260, 2016 | | 2016 |