Robust inference in time series analysis is concerned with developing statistical methods that remain valid under departures from standard model assumptions, such as the presence of heteroskedasticity ...

Cluster-robust inference and estimation methods have emerged as indispensable tools in empirical research, enabling statisticians and economists to draw valid conclusions from data exhibiting ...

Locally Robust Semiparametrically Efficient Bayesian Inference. (Joint with ANDRIY NORETS.) Slides. We propose a framework for making Bayesian parametric models robust to local misspecification.

The NIC (Network Interface Card)/ network adapters is expected to have the highest market share and will experience the highest CAGR over the forecast period. The demand for this segment is growing ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We are still only at the beginning of this AI rollout, where the training of models is still ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...

AI inference uses trained data to enable models to make deductions and decisions. Effective AI inference results in quicker and more accurate model responses. Evaluating AI inference focuses on speed, ...