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Liquid structural state-space models
A proper parametrization of state transition matrices of linear state-space models (SSMs)
followed by standard nonlinearities enables them to efficiently learn representations from …
followed by standard nonlinearities enables them to efficiently learn representations from …
Learning long-term dependencies in irregularly-sampled time series
Recurrent neural networks (RNNs) with continuous-time hidden states are a natural fit for
modeling irregularly-sampled time series. These models, however, face difficulties when the …
modeling irregularly-sampled time series. These models, however, face difficulties when the …
Automated enforcement of SLA for cloud services
Orchestration and management of cloud computing entities necessitate measuring and
analysis of real-time monitored performance metrics. However, decision making in current …
analysis of real-time monitored performance metrics. However, decision making in current …
OpenStack network acceleration scheme for datacenter intelligent applications
L Phan, K Liu - 2018 IEEE 11th International Conference on …, 2018 - ieeexplore.ieee.org
Cloud virtualization and multi-tenant networking provide Infrastructure as a Service (IaaS)
providers a new and innovative way to offer on-demand services to their customers, such as …
providers a new and innovative way to offer on-demand services to their customers, such as …
Mixed-memory rnns for learning long-term dependencies in irregularly sampled time series
Recurrent neural networks (RNNs) with continuous-time hidden states are a natural fit for
modeling irregularly sampled time series. These models, however, face difficulties when the …
modeling irregularly sampled time series. These models, however, face difficulties when the …
On the applicability of the Lead/Lag Ratio in causality assessment
Within the large set of metrics that have been proposed to assess the presence of a causality
relationship between time series, the Lead/Lag Ratio (LLR) has recently attracted increasing …
relationship between time series, the Lead/Lag Ratio (LLR) has recently attracted increasing …