Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In this paper, we explore various approaches for semi-
supervised learning in an end-to-end automatic speech recog-
nition (ASR) framework. The first step in our approach in-
volves training a seed model on the limited amount of labelled
data. Additional u ...
Automated analyses of the outcome of a simulation have been an important part of atomistic modeling since the early days, addressing the need of linking the behavior of individual atoms and the collective properties that are usually the final quantity of i ...
In the Internet of Things (IoT), the large volume of data generated by sensors poses significant computational challenges in resource-constrained environments. Most existing machine learning algorithms are unable to train a proper model using a significant ...
Depth matching well logs acquired from multiple logging passes in a single well has been a longstanding challenge for the industry. The existing approaches employed in commercial platforms are typically based on classical cross-correlation and covariance m ...
Data from animal-borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have b ...
We present a scheme to obtain an inexpensive and reliable estimate of the uncertainty associated with the predictions of a machine-learning model of atomic and molecular properties. The scheme is based on resampling, with multiple models being generated ba ...
High levels of cognitive workload decreases human's performance and leads to failures with catastrophic outcomes in risky missions. Today, reliable cognitive workload detection presents a common major challenge, since the workload is not directly observabl ...
The two-pass information bottleneck (TPIB) based speaker diarization system operates independently on different conversational recordings. TPIB system does not consider previously learned speaker discriminative information while di-arizing new conversation ...
The utilization of online stochastic algorithms is popular in large-scale learning settings due to their ability to compute updates on the fly, without the need to store and process data in large batches. When a constant step-size is used, these algorithms ...
Background Periventricular leukoaraiosis may be an important pathological change in postural instability gait disorder (PIGD), a motor subtype of Parkinson's disease (PD). Clinical diagnosis of PIGD may be challenging for the general neurologist. Purpose T ...