53 research outputs found
Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendations
People break up, miscarry, and lose loved ones. Their online streaming and
shopping recommendations, however, do not necessarily update, and may serve as
unhappy reminders of their loss. When users want to renege on their past
actions, they expect the recommender platforms to erase selective data at the
model level. Ideally, given any specified user history, the recommender can
unwind or "forget", as if the record was not part of training. To that end,
this paper focuses on simple but widely deployed bi-linear models for
recommendations based on matrix completion. Without incurring the cost of
re-training, and without degrading the model unnecessarily, we develop
Unlearn-ALS by making a few key modifications to the fine-tuning procedure
under Alternating Least Squares optimisation, thus applicable to any bi-linear
models regardless of the training procedure. We show that Unlearn-ALS is
consistent with retraining without \emph{any} model degradation and exhibits
rapid convergence, making it suitable for a large class of existing
recommenders.Comment: 8 pages, 8 figure
MimicPlay: Long-Horizon Imitation Learning by Watching Human Play
Imitation learning from human demonstrations is a promising paradigm for
teaching robots manipulation skills in the real world. However, learning
complex long-horizon tasks often requires an unattainable amount of
demonstrations. To reduce the high data requirement, we resort to human play
data - video sequences of people freely interacting with the environment using
their hands. Even with different morphologies, we hypothesize that human play
data contain rich and salient information about physical interactions that can
readily facilitate robot policy learning. Motivated by this, we introduce a
hierarchical learning framework named MimicPlay that learns latent plans from
human play data to guide low-level visuomotor control trained on a small number
of teleoperated demonstrations. With systematic evaluations of 14 long-horizon
manipulation tasks in the real world, we show that MimicPlay outperforms
state-of-the-art imitation learning methods in task success rate,
generalization ability, and robustness to disturbances. Code and videos are
available at https://mimic-play.github.ioComment: 7th Conference on Robot Learning (CoRL 2023 oral presentation
Nanomechanical Resonators: Toward Atomic Scale
The quest for realizing and manipulating ever smaller man-made movable structures and dynamical machines has spurred tremendous endeavors, led to important discoveries, and inspired researchers to venture to new grounds. Scientific feats and technological milestones of miniaturization of mechanical structures have been widely accomplished by advances in machining and sculpturing ever shrinking features out of bulk materials such as silicon. With the flourishing multidisciplinary field of low-dimensional nanomaterials, including one-dimensional (1D) nanowires/nanotubes, and two-dimensional (2D) atomic layers such as graphene/phosphorene, growing interests and sustained efforts have been devoted to creating mechanical devices toward the ultimate limit of miniaturization— genuinely down to the molecular or even atomic scale. These ultrasmall movable structures, particularly nanomechanical resonators that exploit the vibratory motion in these 1D and 2D nano-to-atomic-scale structures, offer exceptional device-level attributes, such as ultralow mass, ultrawide frequency tuning range, broad dynamic range, and ultralow power consumption, thus holding strong promises for both fundamental studies and engineering applications. In this Review, we offer a comprehensive overview and summary of this vibrant field, present the state-of-the-art devices and evaluate their specifications and performance, outline important achievements, and postulate future directions for studying these miniscule yet intriguing molecular-scale machines
Large AI Models in Health Informatics: Applications, Challenges, and the Future
Large AI models, or foundation models, are models recently emerging with
massive scales both parameter-wise and data-wise, the magnitudes of which can
reach beyond billions. Once pretrained, large AI models demonstrate impressive
performance in various downstream tasks. A prime example is ChatGPT, whose
capability has compelled people's imagination about the far-reaching influence
that large AI models can have and their potential to transform different
domains of our lives. In health informatics, the advent of large AI models has
brought new paradigms for the design of methodologies. The scale of multi-modal
data in the biomedical and health domain has been ever-expanding especially
since the community embraced the era of deep learning, which provides the
ground to develop, validate, and advance large AI models for breakthroughs in
health-related areas. This article presents a comprehensive review of large AI
models, from background to their applications. We identify seven key sectors in
which large AI models are applicable and might have substantial influence,
including 1) bioinformatics; 2) medical diagnosis; 3) medical imaging; 4)
medical informatics; 5) medical education; 6) public health; and 7) medical
robotics. We examine their challenges, followed by a critical discussion about
potential future directions and pitfalls of large AI models in transforming the
field of health informatics.Comment: This article has been accepted for publication in IEEE Journal of
Biomedical and Health Informatic
Nanomechanical Resonators: Toward Atomic Scale
The quest for realizing and manipulating ever smaller man-made movable structures and dynamical machines has spurred tremendous endeavors, led to important discoveries, and inspired researchers to venture to previously unexplored grounds. Scientific feats and technological milestones of miniaturization of mechanical structures have been widely accomplished by advances in machining and sculpturing ever shrinking features out of bulk materials such as silicon. With the flourishing multidisciplinary field of low-dimensional nanomaterials, including one-dimensional (1D) nanowires/nanotubes and two-dimensional (2D) atomic layers such as graphene/ phosphorene, growing interests and sustained effort have been devoted to creating mechanical devices toward the ultimate limit of miniaturization--genuinely down to the molecular or even atomic scale. These ultrasmall movable structures, particularly nanomechanical resonators that exploit the vibratory motion in these 1D and 2D nano-to-atomic-scale structures, offer exceptional device-level attributes, such as ultralow mass, ultrawide frequency tuning range, broad dynamic range, and ultralow power consumption, thus holding strong promises for both fundamental studies and engineering applications. In this Review, we offer a comprehensive overview and summary of this vibrant field, present the state-of-the-art devices and evaluate their specifications and performance, outline important achievements, and postulate future directions for studying these miniscule yet intriguing molecular-scale machines
The Immungenicity and Cross-Neutralizing Activity of Enterovirus 71 Vaccine Candidate Strains
This study aimed to evaluate enterovirus 71 (EV-A71) vaccine candidate strains, including their genotypes, immunogenicity and cross-neutralization capacity. From clinical samples, EV-A71 strains were separated by using Vero cells. Six strains were chosen for vaccine candidates, and the sequences were analyzed. To detect the immunogenicity of the strains, we used them to immunize NIH mice at 0 and 14 days. Cytopathic effects (CPE) were examined to determine the EV-A71 neutralizing antibody (NTAb) titer 14 d after the first and second inoculations. To evaluate the cross-neutralizing capacity of the EV-A71 vaccine candidate strains, we tested serum immunized mice with ten EV-A71 genotype strains. Six EV-A71 vaccine candidate strains were identified, all belonging to sub-genotype C4, the prevalent genotype in China. The sequence similarity of the VP1 regions of the six candidate vaccine strains and three approved inactivated vaccines was 97.58%–97.77%, and the VP1 amino acid similarity was 98.65%–99.33%. Experiments were performed to evaluate the immunogenicity and cross-neutralizing activity of the EV-A71 vaccine candidate strains. The strains had good immunogenicity 14 d after two immunizations, inducing an NTAb titer ranging from 1:94 to 1:346. The NTAb seroconversion rates 14 d after one immunization were above 80% (except HB0007), and significantly increased immunogenicity of EV-A71 strains was observed post-inoculation. Furthermore, our candidate vaccine strains had broad cross-neutralizing activity after challenge with ten sub-genotypes of EV-A71. The highest NTAb titer/lowest NTAb titer ratios of sera against EV-A71 sub-genotypes were 8.0 (JS0002), 8.0 (JS0005), 21.3 (HB0005), 21.3 (HB0007), 10.7 (HB0040) and 8.0 (GD0002), respectively. Our EV-A71 strains had good immunogenicity and cross-neutralization activity, and have the potential to serve as vaccine strains for multivalent hand, foot and mouth disease vaccines
Global existence of the finite energy weak solutions to a nematic liquid crystals model
NSF of China [10531020]In this paper, we are concerned with a simplified hydrodynamic equation, proposed by Ericksen and Leslie, modeling the flow of nematic liquid crystals. For a bounded domain in R(3), under the assumption that initial density belongs to L(gamma)(Omega), gamma>3/2, we show the global existence of weak solutions to the nematic liquid crystals model with a penalized system. Furthermore, we also obtain the energy inequality for weak solutions. Copyright (C) 2011 John Wiley & Sons, Ltd
Global existence and optimal L-2 decay rate for the strong solutions to the compressible fluid models of Korteweg type
In this paper, we consider the compressible Navier-Stokes-Korteweg system that models the motions of the compressible isothermal viscous capillary fluids. We prove the global existence of a strong solution to the compressible Navier-Stokes-Korteweg system when the initial perturbation lips parallel to rho(0) - (rho) over cap parallel to(H2) + parallel to u(0)parallel to(H1) is small. Furthermore, if the L-1 norm of the initial perturbation is finite, we can obtain the optimal L-2 decay rates. (C) 2012 Elsevier Inc. All rights reserved.National Natural Science Foundation of China-NSAF of China [10976026
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