Papers
734 papers found
Adaptive Sampling Scheme for Learning in Severely Imbalanced Large Scale Data
Wei Zhang, Said Kobeissi, Scott Tomko et al.
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings
Sami Remes, Markus Heinonen, Samuel Kaski
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors
Zeke Xie, Issei Sato
A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification
Chih-Yang Hsia, Ya Zhu, Chih-Jen Lin
Attentive Path Combination for Knowledge Graph Completion
Xiaotian Jiang, Quan Wang, Baoyuan Qi et al.
A Word Embeddings Informed Focused Topic Model
He Zhao, Lan Du, Wray Buntine
Computer Assisted Composition with Recurrent Neural Networks
Christian Walder, Dongwoo Kim
Data sparse nonparametric regression with $ε$-insensitive losses
Maxime Sangnier, Olivier Fercoq, Florence d’Alché-Buc
Deep Competitive Pathway Networks
Jia-Ren Chang, Yong-Sheng Chen
Distributionally Robust Groupwise Regularization Estimator
Jose Blanchet, Yang Kang
Instance Specific Discriminative Modal Pursuit: A Serialized Approach
Yang Yang, De-Chuan Zhan, Ying Fan et al.
Learning Convolutional Neural Networks using Hybrid Orthogonal Projection and Estimation
Hengyue Pan, Hui Jiang
Learning Deep Semantic Embeddings for Cross-Modal Retrieval
Cuicui Kang, Shengcai Liao, Zhen Li et al.
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks
Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet
Learning RBM with a DC programming Approach
Vidyadhar Upadhya, P. S. Sastry
Limits of End-to-End Learning
Tobias Glasmachers
Locally Smoothed Neural Networks
Liang Pang, Yanyan Lan, Jun Xu et al.
Magnitude-Preserving Ranking for Structured Outputs
Céline Brouard, Eric Bach, Sebastian Böcker et al.
Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems
Vinod Kumar Chauhan, Kalpana Dahiya, Anuj Sharma
Multi-Task Structured Prediction for Entity Analysis: Search-Based Learning Algorithms
Chao Ma, Janardhan Rao Doppa, Prasad Tadepalli et al.
Multi-view Clustering with Adaptively Learned Graph
Hong Tao, Chenping Hou, Jubo Zhu et al.
Nested LSTMs
Joel Ruben Antony Moniz, David Krueger
NeuralPower: Predict and Deploy Energy-Efficient Convolutional Neural Networks
Ermao Cai, Da-Cheng Juan, Dimitrios Stamoulis et al.
One Class Splitting Criteria for Random Forests
Nicolas Goix, Nicolas Drougard, Romain Brault et al.
On the Flatness of Loss Surface for Two-layered ReLU Networks
Jiezhang Cao, Qingyao Wu, Yuguang Yan et al.