Sentence examples for adapts incrementally from inspiring English sources

The phrase "adapts incrementally" is correct and usable in written English.
You can use it when describing a process or system that changes or evolves gradually over time, often in small steps.
Example: "The software adapts incrementally to user feedback, improving its functionality with each update."
Alternatives: "evolves gradually" or "adjusts progressively."

Exact(1)

As an online, knowledge-based intelligent system learns quickly from a large set of data, adapts incrementally in an online mode by interacting continuously with the environment.

Similar(59)

Most companies adapt incrementally and somewhat passively as events unfold.

"Yes, it's been adapted incrementally, but we've never had a moment of systematic reflection".

But the Yale team has advised more nuanced strategies that help communities adapt incrementally.

With a little more aggression and guile, and the ability to adapt incrementally rather than simply bowling and bowling and bowling until the right pitch comes wandering along, he might have become England's own finger-spinning Anil Kumble.

If we look at how globalization has emerged over the past two or three decades, it's been very focused from the north or the west, as it were, large multinational corporations that have developed strategies and products that they only modify or adapt incrementally to sell into emerging markets.

Regular discussions between the UK and the South Asian teams resulted in the intervention being adapted incrementally.

It incrementally adapts, merges and splits segments along a sequence based on the coherence of motion information within each segment.

However, as a user may visit new places over time and we do not know a priori the total number of places a user may visit, we chose to employ a density‐based clustering approach that can incrementally adapts the number of clusters (i.e., the number of unique physical locations) in our system.

However, as a user may visit new places over time and we do not know a priori the total number of places a user may visit, we chose to use a density-based clustering approach that can incrementally adapts the number of clusters (i.e., the number of distinct physical locations).

In the MLLR-based model adaptation, we adopted the unsupervised adaptation method where the acoustic mean models were incrementally adapted with each test utterance.

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