arXiv subjects

Yang Gao

Publications and source records attributed to Yang Gao.

At least 613 records · Page 34Linked to original sources

arXiv2022

On the pragmatism of using binary classifiers over data intensive neural network classifiers for detection of COVID-19 from voice

Lately, there has been a global effort by multiple research groups to detect COVID-19 from voice. Different researchers use different kinds of information from the voice signal to achieve this. Various types of phonated sounds and the sound of cough and breath have all been used with varying degree of success in automated voice-based COVID-19 detection apps. In this paper, we show that detecting COVID-19 from voice does not require custom-made non-standard features or complicated neural network classifiers rather it can be successfully done with just standard features and simple binary classifiers. In fact, we show that the latter is not only more accurate and interpretable but also more computationally efficient in that they can be run locally on small devices. We demonstrate this on a human-curated dataset of over 1000 subjects, collected and calibrated in clinical settings.

cs.SD↗

arXiv2022

Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions

One of the most important AI research questions is to trade off computation versus performance since ``perfect rationality" exists in theory but is impossible to achieve in practice. Recently, Monte-Carlo tree search (MCTS) has attracted considerable attention due to the significant performance improvement in various challenging domains. However, the expensive time cost during search severely restricts its scope for applications. This paper proposes the Virtual MCTS (V-MCTS), a variant of MCTS that spends more search time on harder states and less search time on simpler states adaptively. We give theoretical bounds of the proposed method and evaluate the performance and computations on $9 \times 9$ Go board games and Atari games. Experiments show that our method can achieve comparable performances to the original search algorithm while requiring less than $50\%$ search time on average. We believe that this approach is a viable alternative for tasks under limited time and resources. The code is available at \url{https://github.com/YeWR/V-MCTS.git}.

cs.AI↗

arXiv2022

The Software Stack That Won the Formula Student Driverless Competition

This report describes our approach to design and evaluate a software stack for a race car capable of achieving competitive driving performance in the different disciplines of the Formula Student Driverless. By using a 360° LiDAR and optionally three cameras, we reliably recognize the plastic cones that mark the track boundaries at distances of around 35 m, enabling us to drive at the physical limits of the car. Using a GraphSLAM algorithm, we are able to map these cones with a root-mean-square error of less than 15 cm while driving at speeds of over 70 kph on a narrow track. The high-precision map is used in the trajectory planning to detect the lane boundaries using Delaunay triangulation and a parametric cubic spline. We calculate an optimized trajectory using a minimum curvature approach together with a GGS-diagram that takes the aerodynamics at different velocities into account. To track the target path with accelerations of up to 1.6 g, the control system is split into a PI controller for longitudinal control and model predictive controller for lateral control. Additionally, a low-level optimal control allocation is used. The software is realized in ROS C++ and tested in a custom simulation, as well as on the actual race track.

cs.RO↗

arXiv2022

Planning for Sample Efficient Imitation Learning

Imitation learning is a class of promising policy learning algorithms that is free from many practical issues with reinforcement learning, such as the reward design issue and the exploration hardness. However, the current imitation algorithm struggles to achieve both high performance and high in-environment sample efficiency simultaneously. Behavioral Cloning (BC) does not need in-environment interactions, but it suffers from the covariate shift problem which harms its performance. Adversarial Imitation Learning (AIL) turns imitation learning into a distribution matching problem. It can achieve better performance on some tasks but it requires a large number of in-environment interactions. Inspired by the recent success of EfficientZero in RL, we propose EfficientImitate (EI), a planning-based imitation learning method that can achieve high in-environment sample efficiency and performance simultaneously. Our algorithmic contribution in this paper is two-fold. First, we extend AIL into the MCTS-based RL. Second, we show the seemingly incompatible two classes of imitation algorithms (BC and AIL) can be naturally unified under our framework, enjoying the benefits of both. We benchmark our method not only on the state-based DeepMind Control Suite, but also on the image version which many previous works find highly challenging. Experimental results show that EI achieves state-of-the-art results in performance and sample efficiency. EI shows over 4x gain in performance in the limited sample setting on state-based and image-based tasks and can solve challenging problems like Humanoid, where previous methods fail with small amount of interactions. Our code is available at https://github.com/zhaohengyin/EfficientImitate.

cs.LG↗

arXiv2022

Measurement of the absolute branching fraction of the singly Cabibbo suppressed decay $Λ^{+}_{c}\to pη^{\prime}$

The singly Cabibbo suppressed decay $Λ^{+}_{c}\to pη^{\prime}$ is measured using 4.5 $\mathrm{fb}^{-1}$ of $e^+e^-$ collision data collected at center-of-mass energies between 4.600 and 4.699 GeV with the BESIII detector at BEPCII. Evidence for $Λ^{+}_{c}\to pη^{\prime}$ with a statistical significance of $3.6σ$ is reported with a double-tag approach. The $Λ^{+}_{c}\to pη^{\prime}$ absolute branching fraction is determined to be $(5.62^{+2.46}_{-2.04} \pm 0.26)\times 10^{-4}$, where the first and second uncertainties are statistical and systematic, respectively. Our result is consistent with the branching fraction obtained by the Belle collaboration within the uncertainty of $1σ$.

hep-ex↗

arXiv2022

An Empirical Study on Disentanglement of Negative-free Contrastive Learning

Negative-free contrastive learning methods have attracted a lot of attention with simplicity and impressive performances for large-scale pretraining. However, its disentanglement property remains unexplored. In this paper, we examine negative-free contrastive learning methods to study the disentanglement property empirically. We find that existing disentanglement metrics fail to make meaningful measurements for high-dimensional representation models, so we propose a new disentanglement metric based on Mutual Information between latent representations and data factors. With this proposed metric, we benchmark the disentanglement property of negative-free contrastive learning on both popular synthetic datasets and a real-world dataset CelebA. Our study shows that the investigated methods can learn a well-disentangled subset of representation. As far as we know, we are the first to extend the study of disentangled representation learning to high-dimensional representation space and introduce negative-free contrastive learning methods into this area. The source code of this paper is available at \url{https://github.com/noahcao/disentanglement_lib_med}.

cs.LG↗

arXiv2022

The correlation between WISE 12 $μ$m emission and molecular gas tracers on sub-kpc scales in nearby star-forming galaxies

We complement the MALATANG sample of dense gas in nearby galaxies with archival observations of $^{12}\rm CO$ and its isotopologues to determine scaling relations between Wide-field Infrared Survey Explorer (WISE) 12 $μ$m emission and molecular gas tracers at sub-kiloparsec scales. We find that 12 $μ$m luminosity is more tightly correlated with $^{12}\rm CO$ than it is with $^{13}\rm CO$ or dense gas tracers. Residuals between predicted and observed $^{12}\rm CO$ are only weakly correlated with molecular gas mass surface density ($Σ_{\rm mol}$) in regions where $Σ_{\rm mol}$ is very low ($\sim 10~{\rm M_{\odot}~pc^{-2}}$). Above this limit, the $^{12}\rm CO$ residuals show no correlations with physical conditions of molecular gas, while $^{13}\rm CO$ residuals depend on the gas optical depth and temperature. By analyzing differences from galaxy to galaxy, we confirm that the $^{12}\rm CO$-12 $μ$m relation is strong and statistically robust with respect to star forming galaxies and AGN hosts. These results suggest that WISE 12 $μ$m emission can be used to trace total molecular gas instead of dense molecular gas, likely because polycyclic aromatic hydrocarbons (PAHs, a major contributor to WISE 12 $μ$m~emission) may be well-mixed with the gas that is traced by $^{12}\rm CO$. We propose that WISE 12 $μ$m luminosity can be used to estimate molecular gas surface density for statistical analyses of the star formation process in galaxies.

astro-ph.GA↗

arXiv2022

PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization

Few-shot abstractive summarization has become a challenging task in natural language generation. To support it, we designed a novel soft prompts architecture coupled with a prompt pre-training plus fine-tuning paradigm that is effective and tunes only extremely light parameters. The soft prompts include continuous input embeddings across an encoder and a decoder to fit the structure of the generation models. Importantly, a novel inner-prompt placed in the text is introduced to capture document-level information. The aim is to devote attention to understanding the document that better prompts the model to generate document-related content. The first step in the summarization procedure is to conduct prompt pre-training with self-supervised pseudo-data. This teaches the model basic summarizing capabilities. The model is then fine-tuned with few-shot examples. Experimental results on the CNN/DailyMail and XSum datasets show that our method, with only 0.1% of the parameters, outperforms full-model tuning where all model parameters are tuned. It also surpasses Prompt Tuning by a large margin and delivers competitive results against Prefix-Tuning with 3% of the parameters.

cs.CL↗

arXiv2022

Amplitude analysis and branching fraction measurement of the decay \boldmath $D_{s}^{+} \to K^+π^{+}π^{-}π^{0}$

The singly Cabibbo-suppressed decay $D_{s}^{+} \to K^+π^{+}π^{-}π^{0}$ is observed, using a data set corresponding to an integrated luminosity of 6.32 $\rm fb^{-1}$ recorded by the BESIII detector at the centre-of-mass energies between 4.178 and 4.226 GeV. The first amplitude analysis of $D_{s}^{+} \to K^+π^{+}π^{-}π^{0}$ reveals the sub-structures in this decay and determines the fractions and relative phases of different intermediate processes. The dominant intermediate process is $D_s^+ \to K^{*0}ρ^+$, with a fit fraction of $(40.5\pm2.8_{\rm{stat.}}\pm1.5_{\rm{syst.}})\%$. With the detection efficiency based on our amplitude analysis, the absolute branching fraction for $D_{s}^{+} \to K^+π^{+}π^{-}π^{0}$ is measured to be $(9.75\pm0.54_{\rm{stat.}}\pm0.17_{\rm{syst.}})\times 10^{-3}$.

hep-ex↗

arXiv2022

Automatic transformation of irreducible representations for efficient contraction of tensors with cyclic group symmetry

Tensor contractions are ubiquitous in computational chemistry and physics, where tensors generally represent states or operators and contractions express the algebra of these quantities. In this context, the states and operators often preserve physical conservation laws, which are manifested as group symmetries in the tensors. These group symmetries imply that each tensor has block sparsity and can be stored in a reduced form. For nontrivial contractions, the memory footprint and cost are lowered, respectively, by a linear and a quadratic factor in the number of symmetry sectors. State-of-the-art tensor contraction software libraries exploit this opportunity by iterating over blocks or using general block-sparse tensor representations. Both approaches entail overhead in performance and code complexity. With intuition aided by tensor diagrams, we present a technique, irreducible representation alignment, which enables efficient handling of Abelian group symmetries via only dense tensors, by using contraction-specific reduced forms. This technique yields a general algorithm for arbitrary group symmetric contractions, which we implement in Python and apply to a variety of representative contractions from quantum chemistry and tensor network methods. As a consequence of relying on only dense tensor contractions, we can easily make use of efficient batched matrix multiplication via Intel's MKL and distributed tensor contraction via the Cyclops library, achieving good efficiency and parallel scalability on up to 4096 Knights Landing cores of a supercomputer.

physics.comp-ph↗

arXiv2022

Measurement of the $e^+e^-\toπ^+π^-J/ψ$ cross section in the vicinity of 3.872 GeV

We report a measurement of the cross section for the process $e^+e^-\toπ^+π^-J/ψ$ around the $X(3872)$ mass in search for the direct formation of $e^+e^-\to X(3872)$ through the two-photon fusion process. No enhancement of the cross section is observed at the $X(3872)$ peak and an upper limit on the product of electronic width and branching fraction of $X(3872)\toπ^+π^-J/ψ$ is determined to be $Γ_{ee}\times\mathcal{B}(X(3872)\toπ^+π^-J/ψ)<7.5\times10^{-3}\,\text{eV}$ at $90\,\%$ confidence level under an assumption of total width of $1.19\pm0.21$ MeV. This is an improvement of a factor of about $17$ compared to the previous limit. Furthermore, using the latest result of $\mathcal{B}(X(3872)\toπ^+π^-J/ψ)$, an upper limit on the electronic width $Γ_{ee}$ of $X(3872)$ is obtained to be $<0.32\,\text{eV}$ at the $90\,\%$ confidence level.

hep-ex↗

arXiv2022

Precise Measurements of Decay Parameters and $CP$ Asymmetry with Entangled $Λ-\barΛ$ Pairs

Based on 10 billion $J/ψ$ events collected at the BESIII experiment, a search for $CP$ violation in $Λ$ decay is performed in the difference between $CP$-odd decay parameters $α_{-}$ for $Λ\rightarrow pπ^-$ and $α_{+}$ for $\barΛ\rightarrow \bar{p}π^+$ by using the process $e^+e^- \to J/ψ\rightarrow Λ\barΛ$. With a five-dimensional fit to the full angular distributions of the daughter baryon, the most precise values for the decay parameters are determined to be $α_{-} = 0.7519 \pm 0.0036 \pm 0.0024$ and $α_{+} = -0.7559 \pm 0.0036 \pm 0.0030$, respectively. The $Λ$ and $\barΛ$ averaged value of the decay parameter is extracted to be $α_{\rm{avg}} = 0.7542 \pm 0.0010 \pm 0.0024$ with unprecedented accuracy. The $CP$ asymmetry $A_{CP}=(α_{-}+α_{+})/(α_{-}-α_{+})$ is determined to be $-0.0025 \pm 0.0046 \pm 0.0012$, which is one of the most precise measurements in the baryon sector. The reported results for the decay parameter will play an important role in the studies of the polarizations and $CP$ violations for the strange, charmed and beauty baryons.

hep-ex↗

arXiv2022

Improved measurement of the strong-phase difference $δ_D^{Kπ}$ in quantum-correlated $D\bar{D}$ decays

The decay $D\to K^-π^+$ is studied in a sample of quantum-correlated $D\bar{D}$ pairs, based on a data set corresponding to an integrated luminosity of 2.93\,fb$^{-1}$ collected at the $ψ(3770)$ resonance by the BESIII experiment. The asymmetry between $C\!P$-odd and $C\!P$-even eigenstate decays into $K^-π^+$ is determined to be ${\cal A}_{Kπ} = 0.132 \pm 0.011 \pm 0.007$, where the first uncertainty is statistical and the second is systematic. This measurement is an update of an earlier study exploiting additional tagging modes, including several decay modes involving a $K^0_L$ meson. The branching fractions of the $K^0_L$ modes are determined as input to the analysis in a manner that is independent of any strong phase uncertainty. Using the predominantly $C\!P$-even tag $D\to π^+π^-π^0$ and the ensemble of $C\!P$-odd eigenstate tags, the observable ${\cal A}_{Kπ}^{πππ^0}$ is measured to be $0.130 \pm 0.012 \pm 0.008$. The two asymmetries are sensitive to $r_D^{Kπ} \cos δ_D^{Kπ}$, where $r_D^{Kπ}$ and $δ_D^{Kπ}$ are the ratio of amplitudes and phase difference, respectively, between the doubly Cabibbo-suppressed and Cabibbo-favoured decays. In addition, events containing $D \to K^-π^+$ tagged by $D \to K^0_{S,L} π^+π^-$ are studied in bins of phase space of the three-body decays. This analysis has sensitivity to both $r_D^{Kπ} \cos δ_D^{Kπ}$ and $r_D^{Kπ} \sin δ_D^{Kπ}$. A fit to ${\cal A}_{Kπ}$, ${\cal A}_{Kπ}^{πππ^0}$ and the phase-space distribution of the $D \to K^0_{S,L} π^+π^-$ tags yields $δ_D^{Kπ}= \left( 187.6 {^{+8.9}_{-9.7}}{^{+5.4}_{-6.4}} \right)$ degrees, where external constraints are applied for $r_D^{Kπ}$ and other relevant parameters. This is the most precise measurement of $δ_D^{Kπ}$ in quantum-correlated $D\bar{D}$ decays.

hep-ex↗

arXiv2022

LibFewShot: A Comprehensive Library for Few-shot Learning

Few-shot learning, especially few-shot image classification, has received increasing attention and witnessed significant advances in recent years. Some recent studies implicitly show that many generic techniques or ``tricks'', such as data augmentation, pre-training, knowledge distillation, and self-supervision, may greatly boost the performance of a few-shot learning method. Moreover, different works may employ different software platforms, backbone architectures and input image sizes, making fair comparisons difficult and practitioners struggle with reproducibility. To address these situations, we propose a comprehensive library for few-shot learning (LibFewShot) by re-implementing eighteen state-of-the-art few-shot learning methods in a unified framework with the same single codebase in PyTorch. Furthermore, based on LibFewShot, we provide comprehensive evaluations on multiple benchmarks with various backbone architectures to evaluate common pitfalls and effects of different training tricks. In addition, with respect to the recent doubts on the necessity of meta- or episodic-training mechanism, our evaluation results confirm that such a mechanism is still necessary especially when combined with pre-training. We hope our work can not only lower the barriers for beginners to enter the area of few-shot learning but also elucidate the effects of nontrivial tricks to facilitate intrinsic research on few-shot learning. The source code is available from https://github.com/RL-VIG/LibFewShot.

cs.CV↗

arXiv2022

Observation of resonance structures in $e^+e^-\to π^+π^-ψ_2(3823)$ and mass measurement of $ψ_2(3823)$

Using a data sample corresponding to an integrated luminosity of 11.3 $\rm fb^{-1}$ collected at center-of-mass energies from $4.23$ to $4.70$ GeV with the BESIII detector, we measure the product of the $e^+e^-\to π^+π^-ψ_2(3823)$ cross section and the branching fraction $\mathcal{B}[ψ_2(3823)\to γχ_{c1}]$. For the first time, resonance structure is observed in the cross section line shape of $e^+e^-\to π^+π^-ψ_2(3823)$ with significances exceeding $5σ$. A fit to data with two coherent Breit-Wigner resonances modeling the $\sqrt{s}$-dependent cross section yields $M(R_1)=4406.9\pm 17.2\pm 4.5$ MeV/$c^2$, $Γ(R_1)=128.1\pm 37.2\pm 2.3$ MeV, and $M(R_2)=4647.9\pm 8.6\pm 0.8$ MeV/$c^2$, $Γ(R_2)=33.1\pm 18.6\pm 4.1$ MeV. Though weakly disfavored by the data, a single resonance with $M(R)=4417.5\pm26.2\pm3.5$ MeV/$c^2$, $Γ(R)=245\pm48\pm13$ MeV is also possible to interpret data. This observation deepens our understanding of the nature of the vector charmoniumlike states. The mass of the $ψ_2(3823)$ state is measured as $(3823.12\pm 0.43\pm 0.13)$ MeV/$c^2$, which is the most precise measurement to date.

hep-ex↗

arXiv2022

Observation of the doubly Cabibbo-Suppressed decays $D^+\to K^+π^0π^0$ and $D^+\to K^+π^0η$

By analyzing $e^+e^-$ annihilation data corresponding to an integrated luminosity of $2.93\,\rm fb^{-1}$ collected at the center-of-mass energy of 3.773\,GeV with the BESIII detector, we report the first observations of the doubly Cabibbo-suppressed decays $D^+\to K^+π^0π^0$ and $D^+\to K^+π^0η$. The branching fractions of $D^+\to K^+π^0π^0$ and $D^+\to K^+π^0η$ are measured to be $(2.1 \pm 0.4_{\rm stat} \pm 0.1_{\rm syst})\times 10^{-4}$ and $(2.1 \pm 0.5_{\rm stat} \pm 0.1_{\rm syst})\times 10^{-4}$ with statistical significances of 8.8$σ$ and 5.5$σ$, respectively. In addition, we search for the subprocesses $D^+\to K^{*}(892)^{+}π^0$ and $D^+\to K^{*}(892)^{+}η$ with $K^{*}(892)^+\to K^+π^0$. The branching fraction of $D^+\to K^{*}(892)^{+}η$ is determined to be $({4.4^{+1.8}_{-1.5}}_{\rm stat}\pm0.2_{\rm syst})\times10^{-4}$, with a statistical significance of 3.2$σ$. No significant signal for $D^+\to K^{*}(892)^{+}π^0$ is found and we set an upper limit on the branching fraction of this decay at the 90\% confidence level to be $5.4\times10^{-4}$.

hep-ex↗

arXiv2022

Observation of $η_c(2S) \to 3(π^+π^-)$ and measurements of $χ_{cJ} \to 3(π^+π^-)$ in $ψ(3686)$ radiative transitions

The hadronic decay $η_c(2S) \to 3(π^+π^-)$ is observed with a statistical significance of 9.3 standard deviations using $(448.1\pm2.9)\times10^6$ $ψ(3686)$ events collected by the BESIII detector at the BEPCII collider. The measured mass and width of $η_c(2S)$ are $(3643.4 \pm 2.3 (\rm stat.) \pm 4.4 (\rm syst.))$ MeV/$c^2$ and $(19.8 \pm 3.9 (\rm stat.) \pm 3.1 (\rm syst.))$ MeV, respectively, which are consistent with the world average values within two standard deviations. The product branching fraction $\mathcal{B}[ψ(3686)\to γη_c(2S)]\times\mathcal{B}[η_c(2S)\to3(π^+π^-)]$ is measured to be $(9.2 \pm 1.0 (\rm stat.) \pm 0.9 (\rm syst.))\times10^{-6}$. Using $\mathcal{B}[ψ(3686)\to γη_c(2S)]=(7.0^{+3.4}_{-2.5})\times10^{-4}$, we obtain $\mathcal{B}[η_c(2S) \to 3(π^+π^-)] = (1.31 \pm 0.15 (\rm stat.) \pm 0.13 (\rm syst.)(^{+0.64}_{-0.47}) (\rm extr))\times10^{-2}$, where the third uncertainty is from $\mathcal{B}[ψ(3686) \to γη_c(2S)]$. We also measure the $χ_{cJ} \to 3(π^+π^-)$ ($J=0, 1, 2$) decays via $ψ(3686) \to γχ_{cJ}$ transitions. The branching fractions are $\mathcal{B}[χ_{c0} \to 3(π^+π^-)] = (2.080\pm0.006 (\rm stat.)\pm0.068 (\rm syst.))\times10^{-2}$, $\mathcal{B}[χ_{c1} \to 3(π^+π^-)] = (1.092\pm0.004 (\rm stat.)\pm0.035 (\rm syst.))\times10^{-2}$, and $\mathcal{B}[χ_{c2} \to 3(π^+π^-)] = (1.565\pm0.005 (\rm stat.)\pm0.048 (\rm syst.))\times10^{-2}$.

hep-ex↗

arXiv2022

The cold gas and dust properties of red star-forming galaxies

We study the cold gas and dust properties for a sample of red star forming galaxies called "red misfits." We collect single-dish CO observations and HI observations from representative samples of low-redshift galaxies, as well as our own JCMT CO observations of red misfits. We also obtain SCUBA-2 850 um observations for a subset of these galaxies. With these data we compare the molecular gas, total cold gas, and dust properties of red misfits against those of their blue counterparts ("blue actives") taking non-detections into account using a survival analysis technique. We compare these properties at fixed position in the log SFR-log M* plane, as well as versus offset from the star-forming main sequence. Compared to blue actives, red misfits have slightly longer molecular gas depletion times, similar total gas depletion times, significantly lower molecular- and total-gas mass fractions, lower dust-to-stellar mass ratios, similar dust-to-gas ratios, and a significantly flatter slope in the $\log M_\mathrm{mol}$-$\log M_\star$ plane. Our results suggest that red misfits as a population are likely quenching due to a shortage in gas supply.

astro-ph.GA↗