A New Recursive Least-Squares Method with Multiple Forgetting Schemes

We propose a recursive least-squares method with multiple forgetting schemes to track time-varying model parameters which change with different rates. Our approach hinges on the reformulation of the classic recursive least-squares with forgetting scheme as a regularized least squares problem. A simulation study shows the effectiveness of the proposed method

Memory and cognition in schizophrenia.

Episodic memory deficits are consistently documented as a core aspect of cognitive dysfunction in schizophrenia patients, present from the onset of the illness and strongly associated with functional disability. Over the past decade, research using approaches from experimental cognitive neuroscience revealed disproportionate episodic memory impairments in schizophrenia (Sz) under high cognitive demand relational encoding conditions and relatively unimpaired performance under item-specific encoding conditions. These specific deficits in component processes of episodic memory reflect impaired activation and connectivity within specific elements of frontal-medial temporal lobe circuits, with a central role for the dorsolateral prefrontal cortex (DLPFC), relatively intact function of ventrolateral prefrontal cortex and variable results in the hippocampus. We propose that memory deficits can be understood within the broader context of cognitive deficits in Sz, where impaired DLPFC-related cognitive control has a broad impact across multiple cognitive domains. The therapeutic implications of these findings are discussed

Catastrophic forgetting: still a problem for DNNs

We investigate the performance of DNNs when trained on class-incremental visual problems consisting of initial training, followed by retraining with added visual classes. Catastrophic forgetting (CF) behavior is measured using a new evaluation procedure that aims at an application-oriented view of incremental learning. In particular, it imposes that model selection must be performed on the initial dataset alone, as well as demanding that retraining control be performed only using the retraining dataset, as initial dataset is usually too large to be kept. Experiments are conducted on class-incremental problems derived from MNIST, using a variety of different DNN models, some of them recently proposed to avoid catastrophic forgetting. When comparing our new evaluation procedure to previous approaches for assessing CF, we find their findings are completely negated, and that none of the tested methods can avoid CF in all experiments. This stresses the importance of a realistic empirical measurement procedure for catastrophic forgetting, and the need for further research in incremental learning for DNNs.Comment: 10 pages, 11 figures, Artificial Neural Networks and Machine Learning - ICANN 201

Systematic Fractures

At the end of the road, facing the beach a woman sits in her car, her face dimly lit by her phone screen. While the incessant scroll happens, I observe, ponder, let time and space communicate. As for myself, strewn about the landscape I construct and puzzle. At hand is my own personal catharsis, never forgetting an imagined viewer in the back of my mind. Whether it be through guiding their sight, misleading them, confusing them, obscuring their vision, making them question. Ultimately, I want to play and push boundaries of space and three dimensionality, all the while observing a linearity that dominates our world through the simple construction of time. All of this chopped up in memory and revisited in experiential terms

Managed Forgetting to Support Information Management and Knowledge Work

Trends like digital transformation even intensify the already overwhelming mass of information knowledge workers face in their daily life. To counter this, we have been investigating knowledge work and information management support measures inspired by human forgetting. In this paper, we give an overview of solutions we have found during the last five years as well as challenges that still need to be tackled. Additionally, we share experiences gained with the prototype of a first forgetful information system used 24/7 in our daily work for the last three years. We also address the untapped potential of more explicated user context as well as features inspired by Memory Inhibition, which is our current focus of research.Comment: 10 pages, 2 figures, preprint, final version to appear in KI - K\"unstliche Intelligenz, Special Issue: Intentional Forgettin