Efficient Large-Scale Visual Representation Learning

In this article, we present our approach to single-modality visual representation learning. Understanding visual representations of product content is vital for recommendations, search, and advertising applications in e-commerce. We detail and contrast techniques used to fine-tune large-scale visual representation learning models in an efficient manner under low-resource settings, including several pretrained backbone architectures, both in the convolutional neural network as well as the vision transformer family. We highlight the challenges for e-commerce applications at-scale and highlight the efforts to more efficiently train, evaluate, and serve visual representations. We present ablation studies evaluating the representation offline performance for several downstream tasks, including our visually similar ad recommendations. To this end, we present a novel text-to-image generative offline evaluation method for visually similar recommendation systems. Finally, we include online results from deployed machine learning systems in production at Etsy

adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads

In this article, we present a general approach to personalizing ads through encoding and learning from variable-length sequences of recent user actions and diverse representations. To this end we introduce a three-component module called the adSformer diversifiable personalization module (ADPM) that learns a dynamic user representation. We illustrate the module's effectiveness and flexibility by personalizing the Click-Through Rate (CTR) and Post-Click Conversion Rate (PCCVR) models used in sponsored search. The first component of the ADPM, the adSformer encoder, includes a novel adSformer block which learns the most salient sequence signals. ADPM's second component enriches the learned signal through visual, multimodal, and other pretrained representations. Lastly, the third ADPM "learned on the fly" component further diversifies the signal encoded in the dynamic user representation. The ADPM-personalized CTR and PCCVR models, henceforth referred to as adSformer CTR and adSformer PCCVR, outperform the CTR and PCCVR production baselines by $+2.66\%$ and $+2.42\%$, respectively, in offline Area Under the Receiver Operating Characteristic Curve (ROC-AUC). Following the robust online gains in A/B tests, Etsy Ads deployed the ADPM-personalized sponsored search system to $100\%$ of traffic as of February 2023

Epileptiform Activity in Alcohol Dependent Patients and Possibilities of Its Indirect Measurement

Background: Alcohol dependence during withdrawal and also in abstinent period in many cases is related to reduced inhibitory functions and kindling that may appear in the form of psychosensory symptoms similar to temporal lobe epilepsy frequently in conditions of normal EEG and without seizures. Because temporal lobe epileptic activity tend to spread between hemispheres, it is possible to suppose that measures reflecting interhemispheric information transfer such as electrodermal activity (EDA) might be related to the psychosensory symptoms. Methods and Findings: We have performed measurement of bilateral EDA, psychosensory symptoms (LSCL-33) and alcohol craving (ACQ) in 34 alcohol dependent patients and 32 healthy controls. The results in alcohol dependent patients show that during rest conditions the psychosensory symptoms (LSCL-33) are related to EDA transinformation (PTI) between left and right EDA records (Spearman r = 0.44, p,0.01). Conclusions: The result may present potentially useful clinical finding suggesting a possibility to indirectly assess epileptiform changes in alcohol dependent patients

Subclinical Epileptiform Process in Patients with Unipolar Depression and Its Indirect Psychophysiological Manifestations

BACKGROUND: According to recent clinical findings epileptiform activity in temporolimbic structures may cause depressive and other psychiatric symptoms that may occur independently of any seizure in patient's history. In addition in these patients subclinical seizure-like activity with indirect clinical manifestations likely may occur in a form of various forms of cognitive, affective, memory, sensory, behavioral and somatic symptoms (the so-called complex partial seizure-like symptoms). A typical characteristic of epileptiform changes is increased neural synchrony related to spreading of epileptiform activity between hemispheres even in subclinical conditions i.e. without seizures. These findings suggest a hypothesis that measures reflecting a level of synchronization and information transfer between hemispheres could reflect spreading of epileptiform activity and might be related to complex partial seizure-like symptoms. METHODS AND FINDINGS: Suitable data for such analysis may provide various physiological signals reflecting brain laterality, as for example bilateral electrodermal activity (EDA) that is closely related to limbic modulation influences. With this purpose we have performed measurement and analysis of bilateral EDA and compared the results with psychometric measures of complex partial seizure-like symptoms, depression and actually experienced stress in 44 patients with unipolar depression and 35 healthy controls. The results in unipolar depressive patients show that during rest conditions the patients with higher level of complex partial seizure like symptoms (CPSI) display increased level of EDA transinformation (PTI) calculated between left and right EDA records (Spearman correlation between CPSI and PTI is r = 0.43, p = 0.004). CONCLUSIONS: The result may present potentially useful clinical finding suggesting that increased EDA transinformation (PTI) could indirectly indicate increased neural synchrony as a possible indicator of epileptiform activity in unipolar depressive patients treated by serotoninergic antidepresants