Alexander Jacob Labach

Title: Alexander Jacob Labach and Multi-Event Time-Series Encoding.

Introduction

Alexander Jacob Labach is an inventor based in Toronto, Canada, and works at The Toronto-Dominion Bank. His patent work addresses ways to represent complex time-series data for artificial intelligence and machine-learning systems.

Latest Patents

Labach is associated with 1 patent, titled “Multi-event time-series encoding.” The invention describes aggregating information about each event type across groups of time bins. An event-bin embedding can represent the events of a particular type within a bin, using an aggregated value and the number of events.

The approach combines event-bin embeddings across event types and time bins with an embedding for static data and a representation token. An encoder then uses machine-learning blocks that attend separately to event-focused and time-focused dimensions. The model may first be trained through self-supervised learning with time and event masking, then fine-tuned for specific applications.

Career Highlights

Labach’s patent reflects work on structuring multi-event time-series data so that machine-learning models can process it more effectively. The disclosed method brings together event values, event counts, time-based representations, and static information within an encoder architecture.

Collaborations

The provided information names Saba Zuberi and Maksims Volkovs as Labach’s coworkers. Their inclusion indicates professional connections, but no specific roles in the patent are stated.

Conclusion

Alexander Jacob Labach’s “Multi-event time-series encoding” patent presents a structured approach to preparing complex event data for artificial intelligence and machine learning.