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July 30, 20268 min readInstead of compromising among parameter updates dictated by different training objectives, ControlG allocates computational capacity to objectives sequentially and dynamically. -
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July 9, 202610 min read
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Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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Interspeech 20222022Traditional acoustic echo cancelers require that the reference and microphone signals have exactly the same sampling frequency. In this paper, we present a novel Kalman filtering approach to acoustic echo cancellation (AEC) which blindly accounts for the clock skew between the playback and recording devices without the need for exchanging timestamps when they have independent clocks. The proposed Kalman-filter
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ICML 20222022Current techniques for explaining outliers cannot tell what caused the outliers. We present a formal method to identify “root causes” of outliers, amongst variables. The method requires a causal graph of the variables along with the functional causal model. It quantifies the contribution of each variable to the target outlier score, which explains to what extent each variable is a “root cause” of the target
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SIGIR 2022 Workshop on eCommerce2022Query understanding plays a key role in the search process, and accurate understanding of search queries is the first step toward high-quality search results on e-commerce websites. While head queries with abundant historical data can be easier to interpret, tail queries pose a challenge to accurate understanding. To tackle the challenge, we focus on query rewriting to transform a tail query into a query
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AutoML Conference 20222022We present Syne Tune, a library for large-scale distributed hyperparameter optimization (HPO). Syne Tune’s modular architecture allows users to easily switch between different execution backends to facilitate experimentation and makes it easy to contribute new optimization algorithms. To foster reproducible benchmarking, Syne Tune provides an efficient simulator backend and a benchmarking suite, which are
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NAACL 2022 Workshop on Deep Learning for Low-Resource NLP2022Deep learning methods have enabled task-oriented semantic parsing of increasingly complex utterances. However, a single model is still typically trained and deployed for each task separately, requiring labeled training data for each, which makes it challenging to support new tasks, even within a single business vertical (e.g., food-ordering or travel booking). In this paper we describe Cross-TOP (Cross-Schema
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Gretchen Ertl
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