arXiv research

Paper develops multilingual job classification for ISCO and KZiS.

Study predicts room occupancy using machine learning, achieving high accuracy.

We present a large-scale study of gender bias in occupation classification, a task where the use of machine learning may lead to negative outcomes on peoples' lives. We analyze the potential allocation harms that can result from semantic representation bias. To do so, we study the impact on occupation classification of…

Debiasing techniques can worsen gender bias in text classification, but a tweak improves both.

The paper defines and analyzes Poissonian occupation times for negative Lévy processes.

NDI learns from expert demonstrations by estimating occupancy measures.

Paper analyzes AI's impact on job tasks, predicting future demands.

FORE evaluates occupancy ratios without requiring Bellman completeness.

A new method learns continuous occupancy fields efficiently using the Ising model.

In this short paper, in order to price occupation-time options, such as (double-barrier) step options and quantile options, we derive various joint distributions of a mixed-exponential jump-diffusion process and its occupation times of intervals.

New PCA method detects faults using occupation kernels.

Study measures gender bias in machine translation using multiple reference points.

In this paper, we obtain analytical expression for the distribution of the occupation time in the red (below level $0$) up to an (independent) exponential horizon for spectrally negative Lévy risk processes and refracted spectrally negative Lévy risk processes. This result improves the existing literature in which only…

Digital tools may hinder or facilitate multidisciplinary collaboration in occupational health.

A new method estimates SDEs using occupation kernels.

ROCK method generalizes MOCK for learning dynamical systems efficiently.

Spacematch matches office workers with suitable workspaces based on their preferences.

Method learns SDEs from data snapshots.

We find the optimal investment strategy to minimize the expected time that an individual's wealth stays below zero, the so-called {\it occupation time}. The individual consumes at a constant rate and invests in a Black-Scholes financial market consisting of one riskless and one risky asset, with the risky asset's price…

We introduce cylindrical projections to simulate infinite-dimensional occupation flows of diffusions.

A generalized gamification framework is introduced as a form of smart infrastructure with potential to improve sustainability and energy efficiency by leveraging humans-in-the-loop strategy. The proposed framework enables a Human-Centric Cyber-Physical System using an interface to allow building managers to interact wi…

Building performance discrepancies between building design and operation are one of the causes that lead many new designs fail to achieve their goals and objectives. One of main factors contributing to the discrepancy is occupant behaviors. Occupants responding to a new design are influenced by several factors. Existin…

Develops a new calculus for stochastic processes with occupation flows.

Investment strategies in occupational pension plans are optimized for non-tradable income risk.

Thermal preferences vary from person to person and may change over time. The main objective of this paper is to sequentially pose intelligent queries to occupants in order to optimally learn the indoor air temperature values which maximize their satisfaction. Our central hypothesis is that an occupant's preference rela…

Proposes a game-theoretic framework to motivate energy-efficient behavior in smart buildings.

There is a growing body of work that proposes methods for mitigating bias in machine learning systems. These methods typically rely on access to protected attributes such as race, gender, or age. However, this raises two significant challenges: (1) protected attributes may not be available or it may not be legal to use…

D2SRM solves complex PDEs using deep learning.

DFKI Cabin Simulator tests visual monitoring functions in vehicles.

Occupant behavior (OB) and in particular window openings need to be considered in building performance simulation (BPS), in order to realistically model the indoor climate and energy consumption for heating ventilation and air conditioning (HVAC). However, the proposed OB window opening models are often biased towards …

A modified GAN improves thermal comfort classification models by balancing imbalanced datasets.

Paper uses Sinkhorn distances to improve imitation learning effectiveness.

HCNAF models complex conditional distributions for probabilistic occupancy forecasting.

New conditions prevent gaps in optimal control problems.

This work explores efficient reinforcement learning with density features in low-rank MDPs.

MOCK learns complex systems from trajectories efficiently.

Novel loss function improves few-shot classification performance.

Study shows visual feedback and monetary incentives reduce plugload energy consumption in commercial buildings.

A deep learning model is applied for predicting block-level parking occupancy in real time. The model leverages Graph-Convolutional Neural Networks (GCNN) to extract the spatial relations of traffic flow in large-scale networks, and utilizes Recurrent Neural Networks (RNN) with Long-Short Term Memory (LSTM) to capture …

Accurate classification of self-care problems in children who suffer from physical and motor affliction is an important problem in the healthcare industry. This is a difficult and a time consumming process and it needs the expertise of occupational therapists. In recent years, healthcare professionals have opened up to…

New algorithm reduces dynamic regret for MDPs with unknown transition and adversarial rewards.

Paper tackles dynamic pricing in a geometrically decaying environment, achieving better occupancy with lower rates.

Challenge forecasts EV charging station usage accurately.

Energy consumption for hot water production is a major draw in high efficiency buildings. Optimizing this has typically been approached from a thermodynamics perspective, decoupled from occupant influence. Furthermore, optimization usually presupposes existence of a detailed dynamics model for the hot water system. The…

How do regions acquire the knowledge they need to diversify their economic activities? How does the migration of workers among firms and industries contribute to the diffusion of that knowledge? Here we measure the industry, occupation, and location-specific knowledge carried by workers from one establishment to the ne…

Many modern Artificial Intelligence (AI) systems make use of data embeddings, particularly in the domain of Natural Language Processing (NLP). These embeddings are learnt from data that has been gathered "from the wild" and have been found to contain unwanted biases. In this paper we make three contributions towards me…

DSAC improves cooperative MARL with general utilities, converging faster than existing methods.

Queuing model predicts truck parking occupancy.