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One-Dimensional Handwriting: Inputting Letters and Words on Smart Glasses
TLDR
1D Handwriting is a unistroke gesture technique enabling text entry on a one-dimensional interface that significantly outperforms a selection-based technique for both letter input and word input and has several potential applications for other one- dimensional constrained interfaces.
ForceBoard: Subtle Text Entry Leveraging Pressure
TLDR
The error model of pressure control for successive and error-tolerant input was incorporated into a Bayesian algorithm to infer user input and demonstrated the feasibility of applying pressure as the main channel for text entry.
Value function approximation and model predictive control
TLDR
Two methods of deriving a descriptive final cost function to assist model predictive control (MPC) in selecting a good policy without having to plan as far into the future or having to fine-tune delicate cost functions are explored.
Moving least-squares approximations for linearly-solvable stochastic optimal control problems
TLDR
A new method for finding the principal eigenfunction of a linear operator using a moving least-squares function approximation is described, using efficient iterative solvers that do not require matrix factorization, thereby allowing us to handle large numbers of basis functions.
Aggregation Methods for Lineary-Solvable Markov Decision Process
TLDR
An approximation framework for solving stochastic optimal control problems by using soft state aggregation over a continuous space is presented, enabling us to avoid matrix factorization and take advantage of sparsity by using efficient iterative solvers.
ProxiMic: Convenient Voice Activation via Close-to-Mic Speech Detected by a Single Microphone
TLDR
ProxiMic, a close-to-mic (within 5 cm) speech sensing technique using only one microphone, which a user keeps a microphone-embedded device close to the mouth and speaks directly to the device without wake-up phrases or button presses.
Moving least-squares approximations for linearly-solvable MDP
TLDR
A new framework for finding a solution to Linearly-solvable Markov Decision Process problems on continuous state space by using a moving least-squares approximation, which uses efficient iterative solvers which do not require matrix factorization, so it could handle large numbers of bases.
Spacewalker: Rapid UI Design Exploration Using Lightweight Markup Enhancement and Crowd Genetic Programming
TLDR
Spatewalker allows designers to effectively search a large design space of a UI, using the language they are familiar with, and improve their design rapidly at a minimal cost.
Value function approximation methods for Linearly-solvable Markov Decision Process
Value Function Approximation Methods for Linearly-solvable Markov Decision Process Mingyuan Zhong Chair of the Supervisory Committee: Professor Emanual Todorov Department of Applied Mathematics
New Metrics for Understanding Touch by People with and without Limited Fine Motor Function
TLDR
13 target-agnostic touch performance metrics to characterize what happens during a touch are proposed, which regard a touch as a time series of ovals that occur from finger-down to finger-up.
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