Wasserstein Distance-based Graph Contrastive Learning for Recommendation

Graph contrastive learning (GCL) is able to learn augmentation-invariant representations from raw data and reduce the dependence on labeled data. In the field of recommendation systems, traditional GCL models become a potential solution to insufficient supervision signals by augmenting the user-item interaction graph and optimizing InfoNCE loss to learn user and item representations. However, existing GCL-based recommendation models are limited by dimensional collapse, causing the sub-optimal performance of recommendation models. To tackle this problem, we propose a Wasserstein Distance-based Graph Contrastive Learning model, namely WGCL. Specifically, we integrate the Wasserstein loss into contrastive learning-based recommendation models to align the user/item representations distribution with the isotropic Gaussian distribution, which makes the real distribution of representations more uniform, thereby alleviating dimensional collapse. In fact, Wasserstein loss measures the distinction between the real distribution of entities’ representations and the desired distribution of representations by computing the covariance of representations learned from the augmented views. As a result, Wasserstein distance metric not only enables the representations more uniformly distributed on the hypersphere, but also better preserves the original semantic information of entities. Extensive experiments conducted on three widely used datasets demonstrate that WGCL outperforms traditional recommendation models. Our code is released at https://github.com/Sodapease/WGC

A dynamic programming algorithm for the maximum s-club problem on trees

Computing cliques in an undirected graph G = (V_G, E_G) is a fundamental problem in social network analysis. However, in some cases, the strict definition of a clique (a subset of vertices pairwise adjacent in G) often limits its applicability in real-world settings. To address this issue, we study the s-club: a clique relaxation that induces a subgraph of diameter at most s. Note that a clique is simply a 1-club. Computing a maximum s-club is a computationally challenging problem, as it is NP-hard for any positive integer s in arbitrary graphs. Thus, this paper presents a simple dynamic programming algorithm that efficiently computes a maximum s-club on an n-vertex tree in O(s.n) time. This algorithm outperforms existing algorithms for trees in theory and practice. This approach is a stepping stone towards computing maximum s-clubs on tree-like graphs

Hydroxyl (OH) radical oxidation of surfactant films formed from woodland aerosol particulate material at the air-water interface

Neutron reflectometry was used to examine the reaction of gas-phase hydroxyl radicals with thin surfactant films at the air–water interface. The films comprised insoluble material extracted from aerosol particulate matter collected from the atmosphere of a broadleaf woodland; sampled above and below the canopy across spring, summer, and winter. The measurements presented here act as a proxy for oxidation reactions at the air–water interface of broadleaf woodland atmospheric aqueous aerosols. The material extracted from the woodland atmosphere formed stable surfactant-like thin films at the air–water interface, with maximum thicknesses of 30 Å and neutron scattering length densities between 0.1 × 10−6 Å−2 and 2.5 × 10−6 Å−2. Oxidation by hydroxyl radicals reduced the amount of interfacial material, leaving an oxidation-resistant fraction of 20%–60% of the original film. The values of the surface reaction coefficients, determined by KM-SUB, for the reaction of hydroxyl radicals with woodland films were approximately 10−7 cm2 s−1. Film half-lives were estimated to be 1—2 h in typical day-time hydroxyl radical concentrations and 2 days–1 week in night-time concentrations. Thus, organic material extracted from temperate, broadleaf woodland aerosol can form thin, stable surfactant films at the air–water interface that can be partially removed by the gas-phase hydroxyl radical at a significant enough rate to warrant inclusion in atmospheric models