Zobrazeno 1 - 10
of 2 751
pro vyhledávání: '"Hunt, P. J."'
We present a new method of predicting the ages of galaxies using a machine learning (ML) algorithm with the goal of providing an alternative to traditional methods. We aim to match the ability of traditional models to predict the ages of galaxies by
Externí odkaz:
http://arxiv.org/abs/2402.09857
Autor:
Cao, Hao, Dougherty, Michele K., Hunt, Gregory J., Bunce, Emma J., Christensen, Ulrich R., Khurana, Krishan K., Kivelson, Margaret G.
The last 22.5 orbits of the Cassini mission brought the spacecraft to less than 3000 km from Saturn's 1-bar surface. These close encounters offered an unprecedented view of Saturn's magnetic field, including contributions from the internal dynamo, th
Externí odkaz:
http://arxiv.org/abs/2301.02756
We propose a new class of deep reinforcement learning (RL) algorithms that model latent representations in hyperbolic space. Sequential decision-making requires reasoning about the possible future consequences of current behavior. Consequently, captu
Externí odkaz:
http://arxiv.org/abs/2210.01542
Autor:
Mostaani, E., Hunt, R. J., Thomas, D. M., Szyniszewski, M., Montblanch, A. R. P., Barbone, M., Atature, M., Drummond, N. D., Ferrari, A. C.
The photoluminescence (PL) spectra of monolayer (1L) semiconductors feature peaks ascribed to different charge-carrier complexes. We perform diffusion quantum Monte Carlo simulations of the binding energies of these complexes and examine their respon
Externí odkaz:
http://arxiv.org/abs/2209.01593
Offline reinforcement learning (RL), which aims to learn an optimal policy using a previously collected static dataset, is an important paradigm of RL. Standard RL methods often perform poorly in this regime due to the function approximation errors o
Externí odkaz:
http://arxiv.org/abs/2208.06193
Most recommender systems are myopic, that is they optimize based on the immediate response of the user. This may be misaligned with the true objective, such as creating long term user satisfaction. In this work we focus on mobile push notifications,
Externí odkaz:
http://arxiv.org/abs/2202.08812
Autor:
O'Brien, Conor, Thiagarajan, Arvind, Das, Sourav, Barreto, Rafael, Verma, Chetan, Hsu, Tim, Neufield, James, Hunt, Jonathan J
Online advertising has typically been more personalized than offline advertising, through the use of machine learning models and real-time auctions for ad targeting. One specific task, predicting the likelihood of conversion (i.e.\ the probability a
Externí odkaz:
http://arxiv.org/abs/2201.12666
Autor:
Yue, Yuguang, Xie, Yuanpu, Wu, Huasen, Jia, Haofeng, Zhai, Shaodan, Shi, Wenzhe, Hunt, Jonathan J
Listwise ranking losses have been widely studied in recommender systems. However, new paradigms of content consumption present new challenges for ranking methods. In this work we contribute an analysis of learning to rank for personalized mobile push
Externí odkaz:
http://arxiv.org/abs/2201.07681
Coherent anti-Stokes Raman Spectroscopy (CARS) is a laser-based measurement technique widely applied across many science and engineering disciplines to perform non-intrusive gas diagnostics. CARS is often used to study combustion, where the measured
Externí odkaz:
http://arxiv.org/abs/2111.00917