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Found 9 papers, 2 papers with code
SmartChoices: Augmenting Software with Learned Implementations
We are living in a golden age of machine learning.
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV) technology, allowing the SDV to operate safely and efficiently in its environment.
Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization
Motivated by our sales prediction problem, we propose a factor-based algorithm that is able to take time into account.
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
Autonomous driving presents one of the largest problems that the robotics and artificial intelligence communities are facing at the moment, both in terms of difficulty and potential societal impact.
Active Learning for Cost-Sensitive Classification
We design an active learning algorithm for cost-sensitive multiclass classification: problems where different errors have different costs.
Active Learning with Oracle Epiphany
We present a theoretical analysis of active learning with more realistic interactions with human oracles.
Efficient and Parsimonious Agnostic Active Learning
We develop a new active learning algorithm for the streaming setting satisfying three important properties: 1) It provably works for any classifier representation and classification problem including those with severe noise.
Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition
Under that framework, we identify reasonable assumptions on the generative process of non-sequence data, and propose learning algorithms based on the tensor decomposition method \cite{anandkumar2012tensor} to \textit{provably} recover first-order Markov models and hidden Markov models.
Learning Auto-regressive Models from Sequence and Non-sequence Data
Vector Auto-regressive models (VAR) are useful tools for analyzing time series data.
