Shu Li, Peter Bühlmann
Randomized trials and observational studies, more often than not, run over a certain period of time. The treatment effect evolves during this period which provides crucial insights into the treatment response and the long-term effects. Many conventional methods for estimating treatment effects are limited to the i.i.d. setting and are not suited for inferring the time dynamics of the treatment effect. The time series encountered in these settings are highly informative but often nonstationary due to the changing effects of treatment. This increases the difficulty, since stationarity, a common assumption in time series analysis, cannot be reasonably assumed. Another challenge is the heterogeneity of the treatment effect when the treatment affects units differently. The task of estimating heterogeneous treatment effects from nonstationary and, in particular, interventional time series is highly relevant but has remained unexplored yet. We propose Causal Transfer, a method which combines regression to adjust for confounding with time series modelling to learn the effect of the treatment and how it evolves over time. Causal Transfer does not assume the data to be stationary and can be applied to randomized trials and observational studies in which treatment is confounded. Causal Transfer adjusts the effect for possible confounders and transfers the learned effect to other time series and, thereby, estimates various forms of treatment effects, such as the average treatment effect (ATE) or the conditional average treatment effect (CATE). By learning the time dynamics of the effect, Causal Transfer can also predict the treatment effect for unobserved future time points and determine the long-term consequences of treatment.
Shu Li
These proceedings summarize the latest progress by the ATLAS Experiment at the LHC in measuring diboson production and related searches for physics beyond Standard Model via anomalous gauge couplings with the latest Effective Field Theory approach. The most recent measurements of $W^{+}W^{-} \to \ell^{+}ν\ell^{-}\barν$, $W^{\pm}Z \to 3\ell1ν$ and $Z(\to \ell^{+}\ell^{-})γ$ measurements with ATLAS full Run 2 dataset are presented, along with the highlights of the first evidence of $W^{+}W^{-}$ charge asymmetry, the first measurement of CP-violation sensitive observables in $WZ$, and, for the first time at the LHC, $SU(2)_L \otimes U(1)_Y$ fully gauge invariant anomalous neutral triple gauge coupling limits with $Z(\to \ell^{+}\ell^{-})γ$ process.
Yunxiao Shan, Shu Li, Fuxiang Li, Yuxin Cui, Shuai Li, Ming Zhou, Xiang Li
Density peaks clustering has become a nova of clustering algorithm because of its simplicity and practicality. However, there is one main drawback: it is time-consuming due to its high computational complexity. Herein, a density peaks clustering algorithm with sparse search and K-d tree is developed to solve this problem. Firstly, a sparse distance matrix is calculated by using K-d tree to replace the original full rank distance matrix, so as to accelerate the calculation of local density. Secondly, a sparse search strategy is proposed to accelerate the computation of relative-separation with the intersection between the set of $k$ nearest neighbors and the set consisting of the data points with larger local density for any data point. Furthermore, a second-order difference method for decision values is adopted to determine the cluster centers adaptively. Finally, experiments are carried out on datasets with different distribution characteristics, by comparing with other six state-of-the-art clustering algorithms. It is proved that the algorithm can effectively reduce the computational complexity of the original DPC from $O(n^2K)$ to $O(n(n^{1-1/K}+k))$. Especially for larger datasets, the efficiency is elevated more remarkably. Moreover, the clustering accuracy is also improved to a certain extent. Therefore, it can be concluded that the overall performance of the newly proposed algorithm is excellent.
Shu Li
Proceeding for LHCP2017 conference. Referencing the paper of JHEP07(2017)107
Shu Li, Robert D. Mawhinney for RBC, UKQCD Collaborations
$K \to π$ and $K \to 0$ weak matrix elements of $ΔS = 1$ operators have been measured in 2+1 flavor domain wall fermion (DWF) QCD on (3 fm)$^3$ lattices with $a^{-1} = 1.73(3)$ GeV. As is well known, using these matrix elements and chiral perturbation theory allows a determination of the $K \to ππ$ matrix elements that enter in the quantitative value for the $ΔI = 1/2$ rule and $ε^\prime/ε$. Two light dynamical sea quark masses have been used, along with six valence quark masses, with the lightest valence quark mass $\approx 1/10$ the physical strange quark mass. We report our results for lattice matrix elements in the $SU(3)_L \times SU(3)_R$ (27,1), (8,1), and (8,8) representations, paying particular attention to the statistical errors achieved after measurements on 75 configurations. We also report on our calculation of the non-perturbative renormalization coefficients for these $ΔS=1$ weak operators, using the Rome-Southampton method.
Shu Li, Honglin He, Jingxuan Yang, Jianming Hu, Yi Zhang, Shuo Feng
Testing and evaluation are critical to the development and deployment of autonomous vehicles (AVs). Given the rarity of safety-critical events such as crashes, millions of tests are typically needed to accurately assess AV safety performance. Although techniques like importance sampling can accelerate this process, it usually still requires too many numbers of tests for field testing. This severely hinders the testing and evaluation process, especially for third-party testers and governmental bodies with very limited testing budgets. The rapid development cycles of AV technology further exacerbate this challenge. To fill this research gap, this paper introduces the few-shot testing (FST) problem and proposes a methodological framework to tackle it. As the testing budget is very limited, usually smaller than 100, the FST method transforms the testing scenario generation problem from probabilistic sampling to deterministic optimization, reducing the uncertainty of testing results. To optimize the selection of testing scenarios, a cross-attention similarity mechanism is proposed to learn to extract the information of AV's testing scenario space. This allows iterative searches for scenarios with the smallest evaluation error, ensuring precise testing within budget constraints. Experimental results in cut-in scenarios demonstrate the effectiveness of the FST method, significantly enhancing accuracy and enabling efficient, precise AV testing.
Shu Li, Binxiang Dai
In this paper, we investigate a Lotka-Volterra competition-diffusion system with self-memory effects and spatial heterogeneity under Dirichlet boundary conditions. We focus on how memory strength influences the coexistence and stability of competing species. By analyzing the characteristic equation, we establish the existence and stability of a spatially nonhomogeneous positive steady state and demonstrate the occurrence of Hopf bifurcation as memory delay increases. Our results reveal that both weak and some opposing memory effects of two competing species promote stable coexistence, while strong memory may destabilize the system and lead to periodic oscillations. Spatial heterogeneity further enriches the dynamical behaviors. Numerical simulations are presented to confirm the theoretical results.
Shu Li
Proceeding for LHCP2017 conference. Referencing the ATLAS publication note: http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2017-005/
Shu Li, Jan Ernest, Peter Bühlmann
Causal inference from observational data is an ambitious but highly relevant task, with diverse applications ranging from natural to social sciences. Within the scope of nonparametric time series, causal inference defined through interventions (cf. Pearl (2000)) is largely unexplored, although time order simplifies the problem substantially. We consider a marginal integration scheme for inferring causal effects from observational time series data, MINT-T (marginal integration in time series), which is an adaptation for time series of a method proposed by Ernest and Bühlmann (Electron. J. Statist, pp. 3155-3194, vol. 9, 2015) for the case of independent data. Our approach for stationary stochastic processes is fully nonparametric and, assuming no instantaneous effects consistently recovers the total causal effect of a single intervention with optimal one-dimensional nonparametric convergence rate $n^{-2/5}$ assuming regularity conditions and twice differentiability of a certain corresponding regression function. Therefore, MINT-T remains largely unaffected by the curse of dimensionality as long as smoothness conditions hold in higher dimensions and it is feasible for a large class of stationary time series, including nonlinear and multivariate processes. For the case with instantaneous effects, we provide a procedure which guards against false positive causal statements.
Shu Li, Jingxuan Yang, Honglin He, Yi Zhang, Jianming Hu, Shuo Feng
Testing and evaluating the safety performance of autonomous vehicles (AVs) is essential before the large-scale deployment. Practically, the number of testing scenarios permissible for a specific AV is severely limited by tight constraints on testing budgets and time. With the restrictions imposed by strictly restricted numbers of tests, existing testing methods often lead to significant uncertainty or difficulty to quantifying evaluation results. In this paper, we formulate this problem for the first time the "few-shot testing" (FST) problem and propose a systematic framework to address this challenge. To alleviate the considerable uncertainty inherent in a small testing scenario set, we frame the FST problem as an optimization problem and search for the testing scenario set based on neighborhood coverage and similarity. Specifically, under the guidance of better generalization ability of the testing scenario set on AVs, we dynamically adjust this set and the contribution of each testing scenario to the evaluation result based on coverage, leveraging the prior information of surrogate models (SMs). With certain hypotheses on SMs, a theoretical upper bound of evaluation error is established to verify the sufficiency of evaluation accuracy within the given limited number of tests. The experiment results on cut-in scenarios demonstrate a notable reduction in evaluation error and variance of our method compared to conventional testing methods, especially for situations with a strict limit on the number of scenarios.
Emma Yu Jin, Shu Xiao Li
Two skew diagrams are defined to be equivalent if their corresponding skew Schur functions are equal. The equivalence classes for ribbons have been classified by Billera, Thomas and van Willigenburg in 2006. In this paper, we provide a complete characterization of equivalence classes for connected skew diagrams with exactly one $2\times m$ or $m\times 2$ block of boxes for all $m\ge 2$. In particular, possible sizes of equivalence classes are one, two or four, confirming special cases of the elusive conjecture on equivalent skew connected diagrams proposed by McNamara and van Willigenburg in 2009.
Nantel Bergeron, Rafael S. González D'León, Shu Xiao Li, C. Y. Amy Pang, Yannic Vargas
We construct three new combinatorial Hopf algebras based on the Loday-Ronco operations on planar binary trees. The first and second algebras are defined on planar trees and labeled planar trees extending the Loday-Ronco and Malvenuto-Reutenauer Hopf algebras respectively. We show that the latter is bidendriform which implies that is also free, cofree, and self-dual. The third algebra involves a new visualization of parking functions as decorated binary trees; it is also bidendriform, free, cofree, and self-dual, and therefore abstractly isomorphic to the algebra PQSym of Novelli and Thibon. We define partial orders on the objects indexing each of these three Hopf algebras, one of which, when restricting to (m+1)-ary trees, coarsens the m-Tamari order of Bergeron and Préville-Ratelle. We show that multiplication of dual fundamental basis elements are given by intervals in each of these orders. Finally, we use an axiomatized version of the techniques of Aguiar and Sottile on the Malvenuto-Reutenauer Hopf algebra to define a monomial basis on each of our Hopf algebras, and to show that comultiplication is cofree on the monomial elements. This in particular, implies the cofreeness of the Hopf algebra on planar trees. We also find explicit positive formulas for the multiplication on monomial basis and a cancellation-free and grouping-free formula for the antipode of monomial elements.
Farid Aliniaeifard, Shu Xiao Li, Stephanie van Willigenburg
We define vertex-colourings for edge-partitioned digraphs, which unify the theory of P-partitions and proper vertex-colourings of graphs. We use our vertex-colourings to define generalized chromatic functions, which merge the chromatic symmetric and quasisymmetric functions of graphs and generating functions of P-partitions. Moreover, numerous classical bases of symmetric and quasisymmetric functions, both in commuting and noncommuting variables, can be realized as special cases of our generalized chromatic functions. We also establish product and coproduct formulas for our functions. Additionally, we construct the new Hopf algebra of r-quasisymmetric functions in noncommuting variables, and apply our functions to confirm its Hopf structure, and establish natural bases for it.
Shu Xiao Li
The immaculate functions, $\mathfrak{S}_α$, were introduced as a Schur-like basis for $\operatorname{\mathsf{Nsym}}$. We investigate facts about their structure constants. These are analogues of Littlewood-Richardson coefficents. We will give a new proof of the left Pieri rule for the $\mathfrak{S}_α$, a translation invariance property for the structure coefficients of the $\mathfrak{S}_α$, and a counterexample to an $\mathfrak{S}_α$-analogue of the saturation conjecture.
Shu Xiao Li
In 2004, J-C. Aval, F. Bergeron and N. Bergeron studied the algebra of diagonally quasi-symmetric functions $\operatorname{\mathsf{DQSym}}$ in the ring $\mathbb{Q}[\mathbf{x},\mathbf{y}]$ with two sets of variables. They made conjectures on the structure of the quotient $\mathbb{Q}[\mathbf{x},\mathbf{y}]/\langle\operatorname{\mathsf{DQSym}}^+\rangle$, which is a quasi-symmetric analogue of the diagonal harmonic polynomials. In this paper, we construct a Hilbert basis for this quotient when there are infinitely many variables i.e. $\mathbf{x}=x_1,x_2,\dots$ and $\mathbf{y}=y_1,y_2,\dots$. Then we apply this construction to the case where there are finitely many variables, and compute the second column of its Hilbert matrix.
Farid Aliniaeifard, Shu Xiao Li
The descent-to-peak map serves as a bridge between algebra and combinatorics. We use it as a tool for proving the equidistribution of peak and valley sets of standard Young tableaux with a very short argument. We also introduce a new shuffle basis of quasisymmetric functions whose elements are eigenvectors of the descent-to-peak map. Using this basis, we then extend the notion of the peak algebra and of the descent-to-peak map to shuffle, tensor, and symmetric algebras.
Farid Aliniaeifard, Shu Xiao Li, Stephanie van Willigenburg
In 2004 Rosas and Sagan asked whether there was a way to define a basis in the algebra of symmetric functions in noncommuting variables, NCSym, having properties analogous to the classical Schur functions. This was because they had constructed a partial such set that was not a basis. We answer their question by defining Schur functions in noncommuting variables using a noncommutative analogue of the Jacobi-Trudi determinant. Our Schur functions in NCSym map to classical Schur functions under commutation, and a subset of them indexed by set partitions forms a basis for NCSym. Amongst other properties, Schur functions in NCSym also satisfy a noncommutative analogue of the product rule for classical Schur functions in terms of skew Schur functions. We also show how Schur functions in NCSym are related to Specht modules, and naturally refine the Rosas-Sagan Schur functions. Moreover, by generalizing Rosas-Sagan Schur functions to skew Schur functions in the natural way, we prove noncommutative analogues of the Littlewood-Richardson rule and coproduct rule for them. Finally, we relate our functions to noncommutative symmetric functions by proving a subset of our functions are natural extensions of noncommutative ribbon Schur functions, and immaculate functions indexed by integer partitions.
Tong Shu Li, Benjamin M. Good, Andrew I. Su
Semantic relation extraction is one of the frontiers of biomedical natural language processing research. Gold standards are key tools for advancing this research. It is challenging to generate these standards because of the high cost of expert time and the difficulty in establishing agreement between annotators. We implemented and evaluated a microtask crowdsourcing approach that can produce a gold standard for extracting drug-disease relations. The aggregated crowd judgment agreed with expert annotations from a pre-existing corpus on 43 of 60 sentences tested. The levels of crowd agreement varied in a similar manner to the levels of agreement among the original expert annotators. This work rein-forces the power of crowdsourcing in the process of assembling gold standards for relation extraction. Further, it high-lights the importance of exposing the levels of agreement between human annotators, expert or crowd, in gold standard corpora as these are reproducible signals indicating ambiguities in the data or in the annotation guidelines.
Farid Aliniaeifard, Shu Xiao Li
In a study, published in \emph{Nature}, researchers from DeepMind and mathematicians demonstrated a general framework using machine learning to make conjectures in pure mathematics. Their work uses neural networks and attribution techniques to guide human intuition towards making provable conjectures. Here, we build upon this framework to develop a method for identifying sufficient conditions that imply a given mathematical statement. Our approach trains neural networks with a custom loss function that prioritizes high precision. Then uses attribution techniques and exploratory data analysis to make conjectures. As a demonstration, we apply this process to Stanley's problem of $e$-positivity of graphs--a problem that has been at the center of algebraic combinatorics for the past three decades. Guided by AI, we rediscover that one sufficient condition for a graph to be $e$-positive is that it is co-triangle-free, and that the number of claws is the most important factor for $e$-positivity. Based on the most important factors in Saliency Map analysis of neural networks, we suggest that the classification of $e$-positive graphs is more related to continuous graph invariants rather than the discrete ones. Furthermore, using neural networks and exploratory data analysis, we show that the claw-free and claw-contractible-free graphs with $10$ and $11$ vertices are $e$-positive, resolving a conjecture by Dahlberg, Foley, and van Willigenburg.
Farid Aliniaeifard, Shu Xiao Li
The well-known descent-to-peak map $Θ_{\mathrm{QSym}}$ for the Hopf algebra of quasisymmetric functions, $\mathrm{QSym}$, and the peak algebra $Π$ were originally defined by Stembridge in 1997. We introduce their noncommutative analogues, the labelled descent-to-peak map $Θ_{\mathrm{NCQSym}}$ for the Hopf algebra of quasisymmetric functions in noncommuting variables, $\mathrm{NCQSym}$, and the peak algebra in noncommuting variables $\mathrm{NC}Π$. Then, we define the Hopf algebra of Schur $Q$-functions in noncommuting variables. We show that our generalizations possess many properties analogous to their classical counterparts. Furthermore, we show that the coefficients in the expansion of certain elements of $\mathrm{NC}Π$ in the monomial basis of $\mathrm{NCQSym}$ satisfy the generalized Dehn-Sommerville equation of Bayer and Billera. In the end, we give representation-theoretic interpretations of the descent-to-peak map for the Hopf algebras of symmetric functions and noncommutative symmetric functions.