More Like this

1. We investigate a novel duality for scalar Gaussian multiple access channels and broadcast channels. The duality we explore is based on shared partial information quantities (e.g. synergy and redundancy). Using lattice theory, we establish a crossover correspondence of the synergistic and redundant components between these two channels. The dual channels are similar to the traditional pairs based on capacity regions, though the pairs we identify have equal transmission powers instead of a sum constraint relating transmission powers.

   Niu, Xueyan ; Quinn, Christopher J. ( January 2020 , International Symposium on Information Theory and Its Applications)

   null (Ed.)
2. Abstract Graph Neural Networks (GNNs) have shown satisfying performance on various graph learning tasks. To achieve better fitting capability, most GNNs are with a large number of parameters, which makes these GNNs computationally expensive. Therefore, it is difficult to deploy them onto edge devices with scarce computational resources, e.g., mobile phones and wearable smart devices. Knowledge Distillation (KD) is a common solution to compress GNNs, where a light-weighted model (i.e., the student model) is encouraged to mimic the behavior of a computationally expensive GNN (i.e., the teacher GNN model). Nevertheless, most existing GNN-based KD methods lack fairness consideration. As a consequence, the student model usually inherits and even exaggerates the bias from the teacher GNN. To handle such a problem, we take initial steps towards fair knowledge distillation for GNNs. Specifically, we first formulate a novel problem of fair knowledge distillation for GNN-based teacher-student frameworks. Then we propose a principled framework named RELIANT to mitigate the bias exhibited by the student model. Notably the design of RELIANT is decoupled from any specific teacher and student model structures, and thus can be easily adapted to various GNN-based KD frameworks. We perform extensive experiments on multiple real-world datasets, which corroborates that RELIANT achieves less biased GNN knowledge distillation while maintaining high prediction utility. Open-source code can be found at https://github.com/yushundong/RELIANT.

   Dong, Yushun ; Zhang, Binichi ; Yuan, Yiling ; Zou, Na ; Wang, Qi ; Li, Jundong ( January 2023 , Proceedings of the 2023 SIAM International Conference on Data Mining (SDM))
3. Adaptive quantum/molecular mechanics: what have we learned, where are we, and where do we go from here?: Adaptive QM/MM

   https://doi.org/10.1002/wcms.1310  

   Duster, Adam W. ; Wang, Chun-Hung ; Garza, Christina M. ; Miller, Danielle E. ; Lin, Hai ( September 2017 , Wiley Interdisciplinary Reviews: Computational Molecular Science)
4. Craniofacial skeletal response to encephalization: How do we know what we think we know?

   https://doi.org/10.1002/ajpa.23766  

   Lesciotto, Kate M. ; Richtsmeier, Joan T. ( January 2019 , American Journal of Physical Anthropology)

   Dramatic changes in cranial capacity have characterized human evolution. Important evolutionary hypotheses, such as the spatial packing hypothesis, assert that increases in relative brain size (encephalization) have caused alterations to the modern human skull, resulting in a suite of traits unique among extant primates, including a domed cranial vault, highly flexed cranial base, and retracted facial skeleton. Most prior studies have used fossil or comparative primate data to establish correlations between brain size and cranial form, but the mechanistic basis for how changes in brain size impact the overall shape of the skull resulting in these cranial traits remains obscure and has only rarely been investigated critically. We argue that understanding how changes in human skull morphology could have resulted from increased encephalization requires the direct testing of hypotheses relating to interaction of embryonic development of the bones of the skull and the brain. Fossil and comparative primate data have thoroughly described the patterns of association between brain size and skull morphology. Here we suggest complementing such existing datasets with experiments focused on mechanisms responsible for producing the observed patterns to more thoroughly understand the role of encephalization in shaping the modern human skull.

    

   more » « less
5. What Do We Mean When We Say “Insight”? A Formal Synthesis of Existing Theory

   https://doi.org/10.1109/TVCG.2023.3326698  

   Battle, Leilani ; Ottley, Alvitta ( October 2023 , IEEE Transactions on Visualization and Computer Graphics)