Optimization 其實學乜野
點optimize某objective subject to 唔同constraint (equality or inequality)
幾時有solution, 點計呀etc
深啲既有dynamic optimization, decision making over time etc.
like high school finding local maximum pt/minimum pt
Dynamic programming
讀緊game theory,入面有好多simplex optimization,用手計計到頭暈
Agger 好煩 nash bargaining solution
Dynamic programming 已經好好做。
Behavioral econ 有啲咩multi-selves agent, dynamically inconsistent agent, 連dynamic programming 都唔apply,煩到嘔泡。
Nash bargaining 亦都係最簡單,有幾多relationship中的surplus只係按bargaining power分。
好在我唔係modeling個邊
optimization其實係好正既topic 我做緊machine learning research
Machine learning入面好多algorithm 都係solve optimization problems
當中會用到好多real analysis同functional analysis既techniques
最正個位係可以自己諗某啲algorithms去solve某一類optimization problems然後paper
functional 同 real analysis 都好正
巴打講多啲 QM有好多banach space,想知多啲functional analysis做啲咩
我d FA已經唔記得七七八八 , 我更加唔識物理
某D Linear PDE可以用functional analysis的方法去deduce d property
e.g. compact operators
又可以用黎construct measures, e.g. Haar measure
同埋functional analysis本身會deal with d Banach / Hilbert spaces, 但係數學本身都會遇到呢D spaces, e.g. space of continuous functions, L^p spaces等等
probability都會見到, e.g. weak convergence
所以functional analysis算係analysis的基礎野 又要準備溫書考qualifying
analysis好難讀 巴打一定好醒目
我只係數學系的地底泥