arXiv research

The paper presents a method to reduce arm motion complexity for prosthetics and robotics.

Study local exploration on dynamic graphs with time-varying edges.

New metric solves correspondence problem for robotic arm imitation learning.

Robots can rapidly acquire new skills from demonstrations. However, during generalisation of skills or transitioning across fundamentally different skills, it is unclear whether the robot has the necessary knowledge to perform the task. Failing to detect missing information often leads to abrupt movements or to collisi…

High quality reconstruction with interventional C-arm cone-beam computed tomography (CBCT) requires exact geometry information. If the geometry information is corrupted, e. g., by unexpected patient or system movement, the measured signal is misplaced in the backprojection operation. With prolonged acquisition times of…

In recent years, air traffic communication data has become easy to access, enabling novel research in many fields. Exploiting this new data source, a wide range of applications have emerged, from weather forecasting to stock market prediction, or the collection of information about military and government movements. Ty…

Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly…

FineHand learns hand shapes for better ASL recognition.

Rehabilitation training is the primary intervention to improve motor recovery after stroke, but a tool to measure functional training does not currently exist. To bridge this gap, we previously developed an approach to classify functional movement primitives using wearable sensors and a machine learning (ML) algorithm.…

Paper reduces movement primitive dimensionality in parameter space.

Infants' spontaneous and voluntary movements mirror developmental integrity of brain networks since they require coordinated activation of multiple sites in the central nervous system. Accordingly, early detection of infants with atypical motor development holds promise for recognizing those infants who are at risk for…

We recast the Calabi flow in DeGiorgi's language of minimizing movements. We establish the long time existence of minimizing movements for K-energy with arbitrary initial condition. Furthermore we establish some a priori regularity of these solutions, and that sufficiently regular minimizing movements are smooth soluti…

Taureau uses Twitter sentiment analysis to predict stock market movement.

Neural nets predict user attention from mouse movements.

Paper proves minimizing movements match smooth droplet flow in 3D.

MPANF improves naive forecast by incorporating directional information.

We study involuntary micro-movements of the eye for biometric identification. While prior studies extract lower-frequency macro-movements from the output of video-based eye-tracking systems and engineer explicit features of these macro-movements, we develop a deep convolutional architecture that processes the raw eye-t…

Neuroscientific studies of drawing-like movements usually analyze neural representation of either geometric (eg. direction, shape) or temporal (eg. speed) features of trajectories rather than trajectory's representation as a whole. This work is about empirically supported mathematical ideas behind splitting and merging…

Study identifies key trades predicting market movements.

The study introduces a new stickiness parameter for stock prices using a non-linear model.

The rise of non-linear and interactive media such as video games has increased the need for automatic movement animation generation. In this survey, we review and analyze different aspects of building automatic movement generation systems using machine learning techniques and motion capture data. We cover topics such a…

Bayesian method infers local rules for collective animal movement.

Optimizing data movement significantly improves transformer training efficiency.

NoTMF forecasts sparse urban road movement speeds with nonstationary temporal matrix factorization.

Study on pseudo-Riemannian Bertrand manifolds finds no closed movement systems.

Study identifies personality traits from dance movements in music.

We study a bad arm existing checking problem in which a player's task is to judge whether a positive arm exists or not among given K arms by drawing as small number of arms as possible. Here, an arm is positive if its expected loss suffered by drawing the arm is at least a given threshold. This problem is a formalizati…

New algorithms for streaming bandits with limited memory.

Study best arm identification in restless Markov multi-armed bandits with state-dependent transitions.

New algorithm reduces dynamic regret in time-varying movement costs.

Paper tackles identifying an odd arm in a multi-armed bandit with restless Markov processes and trembling hand.

Generically learns movement control policies from exploration data.

Study on droplet flow on uneven surfaces, proving existence and properties.

Improved theoretical guarantees for Top Two algorithms.

We address the M-best-arm identification problem in multi-armed bandits. A player has a limited budget to explore K arms (M<K), and once pulled, each arm yields a reward drawn (independently) from a fixed, unknown distribution. The goal is to find the top M arms in the sense of expected reward. We develop an algorithm …

Framework analyzes stock price co-movement with fundamentals using big data.

Sequential screening and dynamic regret in multi-armed bandits with arriving arms

Paper tackles good arm identification in stochastic bandits.

We consider the best-arm identification problem in multi-armed bandits, which focuses purely on exploration. A player is given a fixed budget to explore a finite set of arms, and the rewards of each arm are drawn independently from a fixed, unknown distribution. The player aims to identify the arm with the largest expe…

Alternative proof of weak solutions to mean curvature flow using minimizing movements.

A novel algorithm reduces communication costs in federated best arm identification.

New algorithms identify best arm with less pulls, adapting to arm covariances.

Study best arm identification in restless bandits with unknown TPMs.

New method for identifying best arm in batched multi-armed bandit problems.

Optimal best-arm identification with known number of optimal arms.

We consider a novel multi-armed bandit framework where the rewards obtained by pulling the arms are functions of a common latent random variable. The correlation between arms due to the common random source can be used to design a generalized upper-confidence-bound (UCB) algorithm that identifies certain arms as $non-c…

Paper tackles outlier detection in multi-armed bandits, achieving high accuracy with reduced exploration costs.

Wrist movements can reveal digits, posing security risks.